Znajdź zawartość

Free Download Udemy - Mechanical Engineering Crash Course - 12 Courses In 1 Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 8.07 GB | Duration: 23h 18m Learn Mechanical Engineering concepts like mechanics, fluid mechanics, thermodynamics, machine design and more. What you'll learn Basics of Scientific Method & Engineering Introduction to Mechanical Engineering Core Concepts of Engineering Mechanics including Statics & Dynamics Mechanics of Materials - Concepts of Stress, Strain and Material Behaviour under Force Materials Engineering - Concepts of Materials & its Types Fluid Mechanics - Fluid behaviour and its properties Thermodynamics - How interconversion of thermal and mechanical energy is carried out Thermodynamic Cycles - How Engines and Refrigerators work Machine Element Design - How various common machine elements are designed Heat Transfer - Modes via through which heat transfer occurs and how it is modelled Manufacturing Processes - Introduction to most commonly used manufacturing processes Computer Aided Design - Introduction to CAD using SolidWorks Engineering Simulations - Introduction to FEA and CFD using ANSYS Requirements Basic High School level Physics is recommended. But not essential. Just time and will to learn. Access to Solidworks Version 2018 or higher. (For CAD Section Only) Access to ANSYS Version 2018 or higher. (For Engineering Simulations Section Only) Description Are you ready to dive into the exciting world of Mechanical Engineering?This Crash Course in Mechanical Engineering is designed to equip you with the essential knowledge and skills to excel in this dynamic field. Whether you're a student, a working professional, or an enthusiast, this course offers a comprehensive introduction to the core principles of Mechanical Engineering.This course covers key topics such as thermodynamics, fluid mechanics, robotics, material science, and mechanical design. Through expert-led video lectures, you'll gain a deep understanding of how Mechanical Engineering drives innovation in various industries in the world.This course will serve you either as gateway to Mechanical Engineering if you are new to the field, or it will serve you as a refresher course if you are seasoned professional mechanical engineer.What You'll Learn:Fundamentals of Mechanical EngineeringEngineering MechanicsFluid MechanicsSolid MechanicsMachine Element DesignComputer Aided DesignFinite Element AnalysisComputational Fluid DynamicsManufacturing ProcessesAnd Much More...Why Choose This Course?Flexible Learning: Study at your own pace with lifetime access to course materials.One stop Course for everything Mechanical Engineering: Get quick information about various subtopics of Mechanical Engineering in one courseCertificate of Completion: Earn a certificate to showcase your expertise and boost your career prospects.Take the first step toward becoming a Mechanical Engineering. Whether you're designing the next generation of electric vehicles, optimizing renewable energy systems, or creating cutting-edge robotics, this course will provide the foundation you need to succeed.Mechanical Engineering is the backbone of modern technology, and this course is your gateway to mastering it. Don't wait - start your journey today and unlock endless opportunities in this ever-evolving field!Enrol now and transform your future with Mechanical Engineering! Overview Section 1: Introduction Lecture 1 Message from the Instructor Section 2: Introduction to Engineering Lecture 2 Science & Engineering Lecture 3 Scientific Method Lecture 4 Engineering Disciplines Section 3: Mechanical Engineering Lecture 5 Mechanical Engineering Lecture 6 Mechanical Engineering Skillset Section 4: Engineering Mechanics Lecture 7 Mechanics & its Types Lecture 8 Physical Quantities Lecture 9 Equilibrium & Moments Lecture 10 Free Body Diagrams Lecture 11 Friction Lecture 12 Newton's Laws of Motion Lecture 13 Law of Gravitation Lecture 14 Kinematics Lecture 15 Kinetics Lecture 16 Projectile Motion Lecture 17 Work & Energy Lecture 18 Momentum & Collisions Section 5: Materials Engineering Lecture 19 Materials Science Lecture 20 Mechanical Properties Lecture 21 Types of Materials Lecture 22 Metals Lecture 23 Polymers Lecture 24 Ceramics Lecture 25 Composites Section 6: Mechanics of Materials Lecture 26 Stress & its Types Lecture 27 Cartesian Stress Components Lecture 28 Poisson Ratio & Hooke's Law Lecture 29 Stress Transformation & Mohr Circle Lecture 30 Torsion Lecture 31 Static Failure Lecture 32 Fatigue Failure Lecture 33 Fluctuating Stresses Section 7: Fluid Mechanics Lecture 34 Introduction to Fluid Mechanics Lecture 35 Properties of Fluids Lecture 36 Fluid Statics: Pascal's Law & Buoyancy Lecture 37 Fluid Dynamics I: Continuity Equation Lecture 38 Fluid Dynamics II: Bernoulli Equation Lecture 39 Laminar & Turbulent Flow Lecture 40 Characterizing Fluid Flow Lecture 41 Internal Flow Lecture 42 Open Channel Flow Lecture 43 Turbines & Pumps Section 8: Thermodynamics Lecture 44 Thermodynamics Lecture 45 Thermodynamics Terms Lecture 46 Pure Substance & Phase Diagrams Lecture 47 Gas Laws Lecture 48 First Law of Thermodynamics Lecture 49 Second Law of Thermodynamics Lecture 50 Carnot Engine Lecture 51 Entropy Lecture 52 Thermodynamic Tables Section 9: Thermodynamic Cycles Lecture 53 Thermodynamic Cycles Lecture 54 Rankine Cycle Lecture 55 Brayton Cycle Lecture 56 Vapor Compression Cycle Section 10: Heat Transfer Lecture 57 Heat Transfer & its Modes Lecture 58 Conduction Lecture 59 Convection Lecture 60 Radiation Lecture 61 Thermal Resistance Lecture 62 Heat Exchangers Section 11: Design of Machine Elements Lecture 63 Introduction to Mechanical Design Lecture 64 Design Factor Lecture 65 Machine Elements Lecture 66 Mechanical Shafts Lecture 67 Non-Permanent Joints (Fasteners) Lecture 68 Permanent Joints Lecture 69 Bearings Lecture 70 Gears I - Introduction Lecture 71 Gears II - Force Analysis Lecture 72 Belt Drives Section 12: Manufacturing Processes Lecture 73 Basics of Manufacturing Lecture 74 Primary vs Secondary Manufacturing Processes Lecture 75 Primary Manufacturing Processes Lecture 76 Secondary Manufacturing Processes Lecture 77 Computer Aided Manufacturing (CAM) Section 13: CAD using SolidWorks Lecture 78 CAD vs CAM vs CAE Lecture 79 Introduction to SolidWorks Lecture 80 Sketching in SolidWorks Lecture 81 3D Modelling in SolidWorks Lecture 82 CAD Practice A- Table Parts Lecture 83 CAD Practice B- Table Assembly Lecture 84 Creating Drawings Section 14: Engineering Simulations (ANSYS) Lecture 85 Finite Element Analysis Lecture 86 Theory of FEA Lecture 87 FEA Procedure Lecture 88 Static Structural Analysis Lecture 89 Steady State Thermal Analysis Lecture 90 Computational Fluid Dynamics Lecture 91 Laminar Flow in a Pipe I Lecture 92 Laminar Flow in a Pipe II Lecture 93 Laminar Flow in a Pipe III Mechanical Engineers who want a refresher crash course,Mechanical Engineering Students,Anyone who wants to learn Mechanical Engineering Homepage: https://www.udemy.com/course/mechanical-engineering-crash-course/ [b]AusFile[/b] https://ausfile.com/ajrns9hfieem/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part01.rar.html https://ausfile.com/m420aoyndffu/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part02.rar.html https://ausfile.com/31idm6k2u51y/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part03.rar.html https://ausfile.com/8ttx3rvaz3p1/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part04.rar.html https://ausfile.com/3biqfkhkgrch/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part05.rar.html https://ausfile.com/gwqq5r5d3k1b/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part06.rar.html https://ausfile.com/ut3oqw6x8v2x/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part07.rar.html https://ausfile.com/5mq3wuw1d437/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part08.rar.html https://ausfile.com/s7vorkln1bs3/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part09.rar.html Rapidgator https://rg.to/file/f21b6e47390948e50d2f72e28b3a741a/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part01.rar.html https://rg.to/file/8a16fb51549fc4fd680895128e3bf177/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part02.rar.html https://rg.to/file/ec38c8b7beec581bb37da54a8f3ab19c/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part03.rar.html https://rg.to/file/adbf62bf95f5d4f42a02dd96187f3361/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part04.rar.html https://rg.to/file/822960227480b18283c9019862b3a483/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part05.rar.html https://rg.to/file/7c961664679241159a8f42bfc3587816/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part06.rar.html https://rg.to/file/2d4c781a65417a6896afc72ad7f64c8e/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part07.rar.html https://rg.to/file/aa3a725f6943fc4fd3dc6166d9e62993/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part08.rar.html https://rg.to/file/2f332cab9467cd3c92cce89b84bac89a/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part09.rar.html Fikper Free Download https://fikper.com/2F3hEZ4hyx/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part01.rar.html https://fikper.com/dJz1kqNl1x/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part02.rar.html https://fikper.com/d2H1wlrS0g/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part03.rar.html https://fikper.com/wRA01RmCmE/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part04.rar.html https://fikper.com/ffvJ8gfGGY/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part05.rar.html https://fikper.com/eqgrOkyvEk/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part06.rar.html https://fikper.com/sOujyBK3Us/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part07.rar.html https://fikper.com/FqHmBVZvxL/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part08.rar.html https://fikper.com/befCi38Tih/aadhx.Mechanical.Engineering.Crash.Course.12.Courses.In.1.part09.rar.html No Password - Links are Interchangeable

Free Download Udemy - Computational Science And Engineering 1 Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.61 GB | Duration: 5h 49m Applied Mathematics: Real World Modeling, Differential Equations, and Linear Systems What you'll learn Understand how to identify patterns and structures in a wide range of applications, including engineering, science, economics, and biology. Develop the ability to model real world problems using mathematical equations and techniques. Learn both analytical and numerical methods for solving mathematical equations, including the use of MATLAB. Gain experience in applying mathematical concepts to solve practical, real world problems. Requirements Basic understanding of calculus and differential equations, Some familiarity with MATLAB or a willingness to learn the software, Openness to learning linear algebra mathematical concepts and their applications in various fields Description This course on Computational Science and Engineering focuses on mathematical modeling, differential equations, and linear algebra to solve real-world problems. Students will learn to develop and analyze models for various applications in engineering, physics, and data science. Key topics include the use of the delta function, boundary value problems, and numerical methods.Through hands-on projects and case studies, parti[beeep]nts will gain practical skills in applying mathematical concepts to complex systems, enhancing their problem-solving abilities in diverse fields. The course emphasizes collaborative learning, where students work in teams to tackle real-world challenges, fostering teamwork and communication skills essential in today's workforce.Additionally, students will have access to software tools and programming languages commonly used in the industry, allowing them to implement and test their models effectively. Each module is designed to build upon the previous one, ensuring a comprehensive understanding of the material.By the end of the course, parti[beeep]nts will be equipped with the theoretical knowledge and practical experience needed to confidently approach complex mathematical problems. Join us to explore the intersection of theory and application in applied mathematics, and prepare to make significant contributions to your chosen field! This course concludes by encouraging questions for further clarification in subsequent sessions. This course is designed to appeal to students from a variety of backgrounds, including: Engineering students: The course covers mathematical modeling and problem-solving techniques that are highly relevant to engineering applications. Science students: This course emphasizes the use of mathematics to identify patterns and understand phenomena across different scientific disciplines. Economics and business students: The course touches on the application of mathematics in economic and financial contexts. Biology students: Their's relevance of the course content to biological applications. The course aims to help students, regardless of their previous mathematical experience, to see the broader relevance and applications of mathematics beyond just solving formulas. It provides an opportunity for students to develop a deeper understanding of the patterns and structures that underlie various real world problems. Homepage: https://www.udemy.com/course/computational-science-and-engineering-1/ [b]AusFile[/b] https://ausfile.com/vsegyt6jrs9q/sbrvj.Computational.Science.And.Engineering.1.part1.rar.html https://ausfile.com/kpp3fgwj09j0/sbrvj.Computational.Science.And.Engineering.1.part2.rar.html https://ausfile.com/xklf47y46ic9/sbrvj.Computational.Science.And.Engineering.1.part3.rar.html https://ausfile.com/6jaubpva6nv3/sbrvj.Computational.Science.And.Engineering.1.part4.rar.html https://ausfile.com/7au7ql9cq14q/sbrvj.Computational.Science.And.Engineering.1.part5.rar.html Rapidgator https://rg.to/file/b49f965d8e4b759b62a1034b0a04e67a/sbrvj.Computational.Science.And.Engineering.1.part1.rar.html https://rg.to/file/ffb21e35f3d67871f117cb4c1bde29ee/sbrvj.Computational.Science.And.Engineering.1.part2.rar.html https://rg.to/file/7d2f4eb77a087a73bdafb9f79540b207/sbrvj.Computational.Science.And.Engineering.1.part3.rar.html https://rg.to/file/a29ab38a2e6c44312076d6db11d4f9c8/sbrvj.Computational.Science.And.Engineering.1.part4.rar.html https://rg.to/file/7b0a2d161266d2f92e1305af38cf7156/sbrvj.Computational.Science.And.Engineering.1.part5.rar.html Fikper Free Download https://fikper.com/VkNORfcnuA/sbrvj.Computational.Science.And.Engineering.1.part1.rar.html https://fikper.com/y4OjGdvqPB/sbrvj.Computational.Science.And.Engineering.1.part2.rar.html https://fikper.com/LHVUCtW4My/sbrvj.Computational.Science.And.Engineering.1.part3.rar.html https://fikper.com/8M94yONMRc/sbrvj.Computational.Science.And.Engineering.1.part4.rar.html https://fikper.com/wvETsG5uHg/sbrvj.Computational.Science.And.Engineering.1.part5.rar.html No Password - Links are Interchangeable

Free Download Mastering Deepseek - Prompt Engineering With AI (150 Prompts) Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.29 GB | Duration: 5h 43m Deepseek V3/R1 Model and ChatGPT Comparison: Understand AI fundamentals with Prompts for Entrepreneurs and Employees. What you'll learn Learn the basics of Deepseek AI and how to get precise results with the right prompts. Discover 150+ ready-to-use prompts for business, social media, coding, finance, etc. Create your own Deepseek account and navigate the user interface with confidence. Understand the key differences between Deepseek and other AI tools like ChatGPT. Improve your prompts with clear structures, specific instructions and creative techniques. Use Deepseek to generate automated texts for blogs, social media and product Descriptions. Try Deepseek for professional emails and marketing campaigns. Develop prompts for data analysis, financial reports and research tasks. Learn how to use Deepseek for creative writing - from novels and scripts to poetry. Experiment with prompt chains to handle complex tasks step by step. Find out how Deepseek can be used for automated customer support and communication. Understand AI bias and learn how to use Deepseek fairly and effectively (including censorship criticism). Use Deepseek for coding tasks like writing and improving code. Create prompts that make Deepseek act as different experts. Learn how to use Deepseek for translations and text summaries. Access Deepseek on your smartphone to stay productive on the go. Explore the ethical challenges of AI-generated content and the limits of Deepseek. Discover the future of AI-powered prompt engineering and how to use Deepseek long-term. Requirements You will learn everything you need in this course. Description Are YOU dreaming of...Mastering Deepseek to create powerful and clear prompts?Improving your prompts to get better AI-generated responses?Using over 150 ready-made prompts for all kinds of tasks right away?Getting the most out of Deepseek - whether you're working, studying, running a business, or using it for daily life?Then this course "Mastering Deepseek: Prompt Engineering with AI (150 Prompts)" is perfect for you! From basic skills to advanced strategies, you'll learn how to use Deepseek to its full potential. Use over 150 ready-to-go prompts, make your work easier, and discover helpful tips and tricks - no experience needed!What you will learn:Introduction to Deepseek: Learn the basics of prompt engineering and set up your Deepseek account. Find out what makes Deepseek different from other AI models and why it's special. We'll start with the basics, explain important terms, and show you how to use your first prompts.How to Improve Prompts: Make your prompts better for more accurate answers. Learn how to add examples, give Deepseek specific roles, and understand the difference between simple and detailed prompts. These simple tips will help you get better results right away.150+ Ready-to-Use Deepseek Prompts: Access a big collection of prompts for different areas! From communication, finance, and writing to business, social media, tech support, and fitness - these prompts will help you use Deepseek in your everyday life and work. See how Deepseek can help with learning, social media posts, and even programming.ChatGPT vs. Deepseek - Which is better? : Compare Deepseek with ChatGPT and see which one fits your needs better. We'll look at speed, costs, and performance, test ready-made prompts, and check what each one is good at.Criticism of Deepseek - Is it justified?: How neutral is Deepseek? We'll look at its limits, costs, and availability to see if it's really worth it. We'll also discuss possible biases in AI and where Deepseek may not be the best fit.Using Deepseek on your smartphone: Learn how to use Deepseek on your phone. I'll show you how to sign up, use the app, and test prompts easily on your phone.Why This Course?Simple and Easy to Follow: No matter if you're new to Deepseek or have used it before, this course will help you step by step.Complete and Useful: You'll learn everything from the basics to advanced features to get the best results with Deepseek.Up-to-Date and Practical: Stay up to date with Deepseek and learn how to apply it in real situations.Learn at Your Own Pace: You can watch this course when it works best for you. Whether you're working, studying, or busy with other things, you can learn anywhere and anytime.Discover how to create better prompts and improve AI responses with Deepseek. In this course, you'll get over 150 ready-to-use prompts, useful tips, and easy guides to help you make the most of Deepseek.Sign up now for the course "Mastering Deepseek: Prompt Engineering with AI (150 Prompts)" and start learning today!See you inside!Your Maximilian.- Last Minute Academy - Overview Section 1: Introduction Lecture 1 Welcome Lecture 2 Before we start - one important note! Lecture 3 Why this Course is different from all other courses! Lecture 4 Disclaimer Section 2: Entering the world of AI with Deepseek Lecture 5 AI Basics: What exactly are "Prompts"? Lecture 6 We create a Deepseek Account Lecture 7 Introduction to Deepseek... Let's get started! Section 3: Enter your first prompts in Deepseek Lecture 8 How easy it is to improve each of your prompts Lecture 9 #1 - Integrate examples into the prompts... Lecture 10 #2 - Assign a role to Deepseek... Lecture 11 Structured VS. unstructured prompts - Which is which? Section 4: Different outputs of Deepseek Lecture 12 #1 - Text output (default) Lecture 13 #2 - Table & List Lecture 14 #3 - HTML code Section 5: Daily prompts with Deepseek Lecture 15 Decision-making with Deepseek Lecture 16 Scheduling with Deepseek Lecture 17 Effective time management (thanks to Deepseek!) Lecture 18 Deepseek as a virtual travel assistant and planner Lecture 19 Writing birthday cards (with poems and more!) Section 6: Professional and career prompts with Deepseek Lecture 20 Deepseek as a virtual office assistant (e.g. for emails) Lecture 21 Top 3 priorities for your day-to-day work Lecture 22 Planning events and activities Lecture 23 Cover letter and CV Section 7: Education prompts with Deepseek Lecture 24 Language and grammar check with Deepseek Lecture 25 Summarize books Lecture 26 Mastering research work with Deepseek Lecture 27 Outline for academic papers Lecture 28 Create a Bibliography Lecture 29 Writing work protocols and reports Section 8: Financial Management Prompts with Deepseek Lecture 30 What can I invest in? (Stocks, ETF, P2P etc.) Lecture 31 Develop a suitable investment strategy with Deepseek Section 9: Business prompts with Deepseek Lecture 32 Identify target group (market analysis) Lecture 33 Creating sales scripts for cold calling Lecture 34 Create legally binding contracts (e.g. NDA) Lecture 35 Create converting subject lines for email campaigns Section 10: 150+ Deepseek prompts for you to copy Lecture 36 #1 - General AI usage - Become a prompt pro Lecture 37 #2 - Communication and interpersonal skills Lecture 38 #3 - Personal finance and budgeting Lecture 39 #4 - Creative writing and storytelling Lecture 40 #5 - Learning and studying made easy Lecture 41 #6 - Business and entrepreneurship Lecture 42 #7 - Social media and copywriting Lecture 43 #8 - Deepseek for sales and cold calling Lecture 44 #9 - Legalese... but with Deepseek Lecture 45 #10 - Deepseek for side jobs and earning money Lecture 46 #11 - Deepseek for executives & team management Lecture 47 #12 - Programming and tech support for everyone Lecture 48 #13 - Sport, fitness and health Lecture 49 #14 - Cooking and nutrition with Deepseek Lecture 50 #15 - Deepseek for entertainment and fun Section 11: ChatGPT vs Deepseek - Which AI is better? Lecture 51 What will you find here? Lecture 52 #1 - Architecture & technical differences Lecture 53 #2 - Speed & costs in comparison Lecture 54 #3 - Comparison with ready-made prompts Lecture 55 #4 - API & integration options Lecture 56 Conclusion: Which model for which purpose? Section 12: Criticism of Deepseek - Is it justified? Lecture 57 Censorship & Controversy - What's really behind it? Lecture 58 Limits of AI - Where does Deepseek fail? Lecture 59 AI Bias and Manipulation - How neutral is Deepseek? Lecture 60 Discussion phase: Now it's your turn! Section 13: Using Deepseek on smartphones Lecture 61 Part 1: Registration and introduction to Deepseek Lecture 62 Part 2: Entering sample prompts in Deepseek Section 14: Final words Lecture 63 I need your help... Lecture 64 What is next for you? Section 15: Looking for downloads? You'll find it here! Lecture 65 #1: All resources for "Enter first prompts at Deepseek" Lecture 66 #2: All resources for "Different outputs of Deepseek" Lecture 67 #3: All resources for "Daily prompts with Deepseek" Lecture 68 #4: All resources for "Professional and career prompts with Deepseek" Lecture 69 #5: All resources for "Education prompts with Deepseek" Lecture 70 #6: All resources for "Financial Management Prompts with Deepseek" Lecture 71 #7: All resources for "Business prompts with Deepseek" Lecture 72 #8: All resources for "150+ Deepseek prompts for you to copy" Lecture 73 #9: All resources for "ChatGPT vs Deepseek - Which AI is better?" Lecture 74 #10: All resources for "Criticism of Deepseek - Is it justified?" Everone who wants to understand Deepseek AI and use it effectively for various purposes.,AI-Beginners who want to learn how to optimize prompts and get better results.,Employees who want to integrate Deepseek AI into their daily work to be more productive.,Entrepreneurs who want to use artificial intelligence for marketing, content creation, and much more.,Anyone who wants to unlock the full potential of Deepseek with 150+ ready-to-use prompts for different areas. Homepage: https://www.udemy.com/course/mastering-deepseek-prompt-engineering-with-ai/ [b]AusFile[/b] https://ausfile.com/f4wn4rocwp9a/dxlbr.Mastering.Deepseek.Prompt.Engineering.With.Ai.150.Prompts.part1.rar.html https://ausfile.com/n3ro52uz3xfi/dxlbr.Mastering.Deepseek.Prompt.Engineering.With.Ai.150.Prompts.part2.rar.html Rapidgator https://rg.to/file/d8ad7fcaaa3475ce33dbe8658f20a6b6/dxlbr.Mastering.Deepseek.Prompt.Engineering.With.Ai.150.Prompts.part1.rar.html https://rg.to/file/96e8fdc22c1d6e46536073387ab5250c/dxlbr.Mastering.Deepseek.Prompt.Engineering.With.Ai.150.Prompts.part2.rar.html Fikper Free Download https://fikper.com/rejbg7Vl1U/dxlbr.Mastering.Deepseek.Prompt.Engineering.With.Ai.150.Prompts.part1.rar.html https://fikper.com/Hb1dGeLigI/dxlbr.Mastering.Deepseek.Prompt.Engineering.With.Ai.150.Prompts.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - BIM Essentials & Digital Engineering Skills in Construction Published: 3/2025 Created by: Chartered Engineers MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 11 Lectures ( 1h 21m ) | Size: 1.7 GB Learn how BIM can Drive Efficiency, Improve Project Delivery, and Streamline Communication Across Construction phases What you'll learn Understand the Benefits of BIM: Learn how BIM improves accuracy, reduces waste, increases sustainability, and drives efficiency across every stage of project Master the fundamentals of BIM and its role in modern construction. Learn how BIM enhances collaboration, efficiency, and project management. Discover how BIM improves material selection and resource optimization. Understand how BIM integrates with emerging technologies like AI, machine learning, and robotics. Prepare for career opportunities in digital construction, such as BIM Manager or Digital Engineer. Understand sustainability practices and how BIM supports them. Learn to how BIM visualize construction projects before they begin, using 3D modeling and virtual reality. Requirements No prior BIM experience is required: This course is designed for both beginners and professionals looking to enhance their digital construction skills. Basic construction knowledge: While not mandatory, familiarity with basic construction terminology and processes will be beneficial. Access to a computer with internet: The course is online, and you will need a device that allows access to videos, course materials, and exercises. Willingness to learn: A passion for digital technologies and a drive to implement them in construction practices. Description Course Description:Welcome to BIM Essentials & Digital Engineering Skills in Construction, an immersive course designed to equip you with the essential skills and knowledge required to thrive in the modern, tech-driven construction industry. Building Information Modeling (BIM) is at the heart of the digital transformation occurring in construction, and understanding how to leverage this powerful tool is critical for success.Throughout the course, you will explore the role of BIM in improving project management, sustainability, collaboration, and efficiency. You'll also gain insights into other cutting-edge technologies such as AI, Digital trends, and automation that are shaping the future of construction. By the end of this course, you'll be ready to apply BIM to solve real-world construction challenges, streamline workflows, optimize resource use, and contribute to sustainable construction practices.This course is perfect for construction professionals who want to build their skills in BIM, as well as for those new to the field who want to understand how digital tools are transforming the industry. With 15 comprehensive lessons, real-world examples, and hands-on applications, this course will provide you with the practical knowledge needed to advance in your career and take part in the digital revolution of construction.Course Outcomes:By completing this course, you will:Understand the Benefits of BIM: Learn how BIM improves accuracy, reduces waste, increases sustainability, and drives efficiency across every stage of the project lifecycle.Enhance Project Delivery: Apply BIM to improve project planning, scheduling, design, and collaboration, ensuring projects are delivered on time, within budget, and to the highest standards.Contribute to Sustainability: Use BIM's resource management capabilities to make environmentally conscious decisions that minimize waste and optimize material usage.Solve Real-World Problems: Learn how BIM can be applied to solve challenges in construction, from material selection to managing change and demolition processes.Prepare for Future Technology: Understand the role of emerging technologies like AI, machine learning, and robotics in transforming the construction industry.Course Structure:This course is divided into lessons, each covering a unique aspect of BIM and its applications in the construction industry:Introduction to BIM and Digital Technologies in ConstructionAn Overview of BIM and its growing importance in modern construction. Learn about the digital tools that are transforming the industry, from design through to maintenance.The Role of BIM in SustainabilityUnderstand how BIM helps achieve sustainable construction practices through resource optimization, waste reduction, and energy efficiency.BIM and Resource SelectionLearn how BIM assists in selecting the right materials, optimizing resource use, and making sustainable decisions throughout the lifecycle of a project.BIM and Project Change ManagementHow BIM facilitates efficient project change management, improving coordination and ensuring that projects stay on track despite design alterations or unforeseen challenges.BIM and Demolition PlanningExplore how BIM is used in the demolition process to reduce waste, optimize material reuse, and ensure safe and sustainable decommissioning of buildings.Data Management with BIMLearn how BIM supports data management throughout the construction process, from design to operation, and enhances collaboration among all project stakeholders.Managing Project Risks Using BIMLearn how BIM can identify potential risks early in the project lifecycle, improving project delivery and minimizing unforeseen costs.The Future of BIM in ConstructionExplore the future applications of BIM, including its integration with emerging technologies like AI, machine learning, and robotics, and its potential to revolutionize construction.Career Opportunities in BIM and Digital ConstructionExplore the growing career opportunities in the digital construction sector, the skills required for success, and how to position yourself for a fulfilling career in BIM.Course Certification:Upon successful completion of the course, you will receive a Certification of Completion, which you can share with employers or include on your resume to demonstrate your proficiency in BIM and digital technologies in construction. Who this course is for Construction Professionals: Engineers, architects, project managers, and other industry professionals looking to enhance their digital skills and learn how BIM is transforming construction projects. Students and Recent Graduates: Individuals looking to break into the construction industry and gain practical, in-demand skills in digital technologies and BIM. Career Changers: Those with a background in a different industry but interested in transitioning to a career in construction and digital technologies. BIM Enthusiasts: Individuals with a keen interest in learning how BIM can revolutionize project management, sustainability, and efficiency in construction. Construction Stakeholders: Developers, contractors, and building owners who want to understand the strategic advantages of BIM and digital tools in modern construction. Anyone Interested in Sustainability: If you are passionate about sustainable construction practices and reducing environmental impacts through digital tools, this course is perfect for you. Homepage: https://www.udemy.com/course/bim-essentials-digital-engineering-skills-in-construction/ [b]AusFile[/b] https://ausfile.com/g79e2wb88f9c/mcaqu.BIM.Essentials..Digital.Engineering.Skills.in.Construction.part1.rar.html https://ausfile.com/u48dh4lia1bi/mcaqu.BIM.Essentials..Digital.Engineering.Skills.in.Construction.part2.rar.html Rapidgator https://rg.to/file/2dd152eae314864e632e1cd391ad45ae/mcaqu.BIM.Essentials..Digital.Engineering.Skills.in.Construction.part1.rar.html https://rg.to/file/fe98cc2b83e16a0bfc7d67c4b6faf5ca/mcaqu.BIM.Essentials..Digital.Engineering.Skills.in.Construction.part2.rar.html Fikper Free Download https://fikper.com/9bMuDryPDq/mcaqu.BIM.Essentials..Digital.Engineering.Skills.in.Construction.part2.rar.html https://fikper.com/Kx75wsovHI/mcaqu.BIM.Essentials..Digital.Engineering.Skills.in.Construction.part1.rar.html No Password - Links are Interchangeable

Free Download Databricks - Master Data Engineering, Big Data, Analytics, AI Published: 3/2025 Created by: Uplatz Training MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 52 Lectures ( 53h 3m ) | Size: 24.2 GB Master Databricks for data engineering, analytics, machine learning, and cloud integration with real-world applications. What you'll learn Understand Databricks Architecture - Learn the key components, workspace features, and advantages of Databricks over traditional data platforms. Set Up and Configure Databricks - Create a Databricks workspace, manage clusters, and navigate notebooks for data processing. Perform ETL Operations - Use Apache Spark in Databricks for extracting, transforming, and loading (ETL) large datasets efficiently. Work with Delta Lake - Implement incremental data loading, schema evolution, and time travel features using Delta Lake. Run SQL Queries in Databricks - Utilize Databricks SQL for querying and analyzing structured data, optimizing performance, and creating dashboards. Build and Deploy Machine Learning Models - Use MLflow for model tracking, hyperparameter tuning, and deploying ML models within Databricks. Integrate Databricks with Cloud Services - Connect Databricks with AWS S3, Azure Data Factory, Snowflake, and BI tools like Power BI. Optimize Cluster Performance - Learn auto-scaling, partitioning, bucketing, and performance tuning techniques for handling big data workloads. Implement Real-Time Data Processing - Develop streaming analytics pipelines for IoT and real-time event processing in Databricks. Secure Data in Databricks - Apply role-based access control (RBAC), encryption, and auditing to protect sensitive data. Develop CI/CD Pipelines for Databricks - Automate deployment and testing using GitHub, Azure DevOps, and Databricks REST API. Manage Data Warehousing in Databricks - Design scalable data lakes, data marts, and warehouse architectures for enterprise solutions. Perform Graph and Time Series Analysis - Use GraphFrames for graph processing and time-series forecasting in Databricks. Monitor and Audit Databricks Workloads - Track resource utilization, job performance, and cost optimization strategies for efficient cloud usage. Apply Databricks to Real-World Use Cases - Work on projects like customer segmentation, predictive maintenance, and fraud detection using Databricks. Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Databricks: Master Data Engineering, Big Data, Analytics, AI course by Uplatz.Databricks is a cloud-based data engineering, analytics, and machine learning platform built on Apache Spark. It provides an integrated environment for processing big data, performing analytics, and deploying machine learning models. Databricks simplifies data engineering and collaboration by offering a unified workspace where data engineers, data scientists, and analysts can work together efficiently. It is available on Microsoft Azure, Amazon Web Services, and Google Cloud, making it a versatile choice for enterprises working with large datasets.Databricks is widely used in industries such as finance, healthcare, retail, and technology for handling large-scale data workloads efficiently. It provides a powerful and scalable solution for organizations looking to leverage big data for analytics, machine learning, and business intelligence.How Databricks WorksDatabricks operates as a fully managed, cloud-based platform that automates and optimizes big data processing. The workflow typically involves:Creating a workspace where users manage notebooks, clusters, and data assets.Configuring clusters using Apache Spark for scalable and distributed computing.Importing and processing data from multiple sources, including data lakes, relational databases, and cloud storage.Running analytics and SQL queries using Databricks SQL for high-performance querying and data visualization.Building and deploying machine learning models using MLflow for tracking experiments, hyperparameter tuning, and deployment.Optimizing performance through auto-scaling, caching, and parallel processing to handle large-scale data workloads efficiently.Integrating with cloud services and APIs such as Azure Data Factory, AWS S3, Power BI, Snowflake, and REST APIs for seamless workflows.Core Features of DatabricksUnified data analytics platform combining data engineering, analytics, and machine learning in a single environment.Optimized runtime for Apache Spark, improving performance for big data workloads.Delta Lake for improved data reliability, versioning, and schema evolution in data lakes.Databricks SQL for running high-performance SQL queries and building interactive dashboards.MLflow for streamlined machine learning development, including model tracking, experimentation, and deployment.Auto-scaling clusters that dynamically allocate resources based on workload Requirements.Real-time streaming analytics for processing event-driven data from IoT devices, logs, and real-time applications.Advanced security features, including role-based access control, encryption, and audit logging for compliance.Multi-cloud support with deployment options across AWS, Azure, and Google Cloud.Seamless integration with third-party analytics and business intelligence tools like Power BI, Tableau, and Snowflake.Benefits of Using DatabricksAccelerates data processing by optimizing Spark-based computations for better efficiency.Simplifies data engineering by automating ETL processes, reducing manual intervention.Enhances collaboration by allowing engineers, analysts, and data scientists to work in a shared, cloud-based workspace.Supports AI and machine learning with an integrated framework for training and deploying models at scale.Reduces cloud computing costs through auto-scaling and optimized resource allocation.Ensures data reliability with Delta Lake, enabling ACID transactions and schema enforcement in large datasets.Provides real-time analytics capabilities for fraud detection, IoT applications, and event-driven processing.Offers flexibility with multi-cloud deployment, making it easier to integrate with existing enterprise infrastructure.Meets enterprise security and compliance standards, ensuring data protection and regulatory adherence.Improves business intelligence with Databricks SQL, enabling organizations to gain deeper insights and make data-driven decisions.Databricks - Course Curriculum1. Introduction to DatabricksIntroduction to DatabricksWhat is Databricks? Platform OverviewKey Features of Databricks WorkspaceDatabricks Architecture and ComponentsDatabricks vs Traditional Data Platforms2. Getting Started with DatabricksSetting Up a Databricks WorkspaceDatabricks Notebook BasicsImporting and Organizing Datasets in DatabricksExploring Databricks ClustersDatabricks Community Edition: Features and Limitations3. Data Engineering in DatabricksIntroduction to ETL in DatabricksUsing Apache Spark with DatabricksWorking with Delta Lake in DatabricksIncremental Data Loading Using Delta LakeData Schema Evolution in Databricks4. Data Analysis with DatabricksRunning SQL Queries in DatabricksCreating and Visualizing DashboardsOptimizing Queries in Databricks SQLWorking with Databricks Connect for BI ToolsUsing the Databricks SQL REST API5. Machine Learning & Data ScienceIntroduction to Machine Learning with DatabricksFeature Engineering in DatabricksBuilding ML Models with Databricks MLFlowHyperparameter Tuning in DatabricksDeploying ML Models with Databricks6. Integration and APIsIntegrating Databricks with Azure Data FactoryConnecting Databricks with AWS S3 BucketsDatabricks REST API BasicsConnecting Power BI with DatabricksIntegrating Snowflake with Databricks7. Performance OptimizationUnderstanding Databricks Auto-ScalingCluster Performance Optimization TechniquesPartitioning and Bucketing in DatabricksManaging Metadata with Hive Tables in DatabricksCost Optimization in Databricks8. Security and ComplianceSecuring Data in Databricks Using Role-Based Access Control (RBAC)Setting Up Secure Connections in DatabricksManaging Encryption in DatabricksAuditing and Monitoring in Databricks9. Real-World ApplicationsReal-Time Streaming Analytics with DatabricksData Warehousing Use Cases in DatabricksBuilding Customer Segmentation Models with DatabricksPredictive Maintenance Using DatabricksIoT Data Analysis in Databricks10. Advanced Topics in DatabricksUsing GraphFrames for Graph Processing in DatabricksTime Series Analysis with DatabricksData Lineage Tracking in DatabricksBuilding Custom Libraries for DatabricksCI/CD Pipelines for Databricks Projects11. Closing & Best PracticesBest Practices for Managing Databricks Projects Who this course is for Data Engineers - Professionals working with ETL pipelines, data transformation, and big data processing. Data Scientists - Those looking to use Databricks for machine learning, feature engineering, and predictive analytics. Big Data Analysts - Individuals working with large-scale datasets, SQL queries, and business intelligence tools. Cloud Engineers - Professionals integrating Databricks with AWS, Azure, and Google Cloud for scalable data solutions. Machine Learning Engineers - Those building and deploying ML models using MLflow, hyperparameter tuning, and automation. Business Intelligence Professionals - Users working with Databricks SQL, Power BI, and dashboarding tools. Database Administrators - DBAs managing data lakes, Delta Lake, Hive tables, and metadata in Databricks. Software Engineers - Developers looking to understand Apache Spark, API integrations, and data pipeline automation. AI & IoT Specialists - Professionals working on real-time analytics, IoT data processing, and AI-driven insights. Enterprise Architects - Those designing scalable, cost-effective, and high-performance data platforms. Cloud Data Professionals - Individuals managing data migration, cost optimization, and auto-scaling clusters. Students & Graduates - Learners interested in big data technologies, cloud computing, and machine learning. Finance & Healthcare Analysts - Professionals working with large datasets for fraud detection, risk analysis, and patient insights. Consultants & Freelancers - Independent professionals offering Databricks consulting, cloud data engineering, and analytics solutions. Technology Leaders & Decision Makers - CTOs, data managers, and tech leads looking to implement Databricks for business transformation. Homepage: https://www.udemy.com/course/databricks-expert-course/ Rapidgator https://rg.to/file/df464864ca15559e07aeade2ef3bdc6a/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part01.rar.html https://rg.to/file/f9852f3e29340c330a5d098fada91fb7/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part02.rar.html https://rg.to/file/36025aaa3b01629e88bf6f7b6b482243/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part03.rar.html https://rg.to/file/09a908f3964f8609394b5d44cb107c28/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part04.rar.html https://rg.to/file/bcd93796ad5b8df314923e174578bc94/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part05.rar.html https://rg.to/file/82b1b23ec37ce328ca1e04e27bc3b69f/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part06.rar.html https://rg.to/file/583f32525409bc8509b5d79451c83677/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part07.rar.html https://rg.to/file/d1528b0bce4a392ec567ce56be138fa9/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part08.rar.html https://rg.to/file/89944a4e921e0011e06bbaddf9fdfc2c/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part09.rar.html https://rg.to/file/2b9bfeee5ddf62f2a562a9d6738bcea7/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part10.rar.html https://rg.to/file/257a1bb4722aee9013e82d80401a7f4a/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part11.rar.html https://rg.to/file/da70f40ed78b2f952677204e1391a265/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part12.rar.html https://rg.to/file/c05f8223744d1eed838f3c9d1939494e/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part13.rar.html https://rg.to/file/262950d70a7ddbd41f6090227502b092/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part14.rar.html https://rg.to/file/4c7e34ced72d364c30712e0632a14006/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part15.rar.html https://rg.to/file/a3cdaba7a055b3ff24f88b435b9ae279/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part16.rar.html https://rg.to/file/a603db41948cf47dee058d7c8688cea9/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part17.rar.html https://rg.to/file/a2a8e438c563d55ec2d2678c9040a87e/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part18.rar.html https://rg.to/file/3a2d655447f6b67e57d92884f552ebc6/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part19.rar.html https://rg.to/file/8a05c337b7303d5b594471a60620a0d2/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part20.rar.html https://rg.to/file/f3c52159a6d6e588f76475dce9c0527e/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part21.rar.html https://rg.to/file/eebe18c789bbd69425b1f434f4c5fe90/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part22.rar.html https://rg.to/file/d874427c5b2bea1f9c69d5220928f31f/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part23.rar.html https://rg.to/file/a6df6f620ecb405831a4f1256980a0e7/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part24.rar.html https://rg.to/file/5c78340e04fe67cdc0c82b441fa7d79b/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part25.rar.html Fikper Free Download https://fikper.com/ozF5H29GYc/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part01.rar.html https://fikper.com/MWf9coEHpC/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part02.rar.html https://fikper.com/IJs6skjoRn/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part03.rar.html https://fikper.com/pAC1LhnhZ3/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part04.rar.html https://fikper.com/J0rHRyPjpm/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part05.rar.html https://fikper.com/cxHAiX0joy/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part06.rar.html https://fikper.com/70xkUa1BmP/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part07.rar.html https://fikper.com/nkHbXoTfIa/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part08.rar.html https://fikper.com/ISHDNWoTdp/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part09.rar.html https://fikper.com/Cv9AsQ3J4f/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part10.rar.html https://fikper.com/h4ai5kmYfE/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part11.rar.html https://fikper.com/9snS9336wj/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part12.rar.html https://fikper.com/uYCAX2Iqt7/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part13.rar.html https://fikper.com/6q4vRwvl3C/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part14.rar.html https://fikper.com/IOgQXN6fAX/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part15.rar.html https://fikper.com/FLojbSqDQN/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part16.rar.html https://fikper.com/84OnF8eXDY/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part17.rar.html https://fikper.com/gBLA8esjH5/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part18.rar.html https://fikper.com/Psn66erCiH/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part19.rar.html https://fikper.com/d2ehNN9sIg/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part20.rar.html https://fikper.com/R7wT1LXThC/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part21.rar.html https://fikper.com/y8K4THW7Sn/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part22.rar.html https://fikper.com/eHblLAN8BX/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part23.rar.html https://fikper.com/Z7bhUTaWmS/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part24.rar.html https://fikper.com/SeYSK7MJrA/xvvek.Databricks.Master.Data.Engineering.Big.Data.Analytics.AI.part25.rar.html No Password - Links are Interchangeable

Free Download Applied Physics For Engineering III - Modern Physics Published: 3/2025 Created by: Pedro Portugal MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English | Duration: 25 Lectures ( 4h 49m ) | Size: 2.22 GB Modern Physics for Engineering: Electromagnetism, Quantum Mechanics, and Relativity in Technology What you'll learn Understand Maxwell's equations in electromagnetic systems and their engineering applications Explain the principles of special relativity and their implications for modern technology and high-speed systems. Analyze quantum mechanical concepts and their relevance to advanced materials and nanoscale engineering. Examine the principles of relativity and their practical applications in technology, such as GPS systems and high-energy particle accelerators. Requirements B.S or graduate students, Mechanical engineering, Manufacturing Engineering, Aerospace Engineering, Electronics Engineering, Physics, Technicians with industry experience. Description This course explores the fundamental principles of modern physics and their direct applications in engineering and technology. Divided into four modules, it provides a foundational understanding of electromagnetism, relativity, quantum mechanics, and their role in cutting edge innovations.The first module focuses on electromagnetism, beginning with Maxwell's equations, which describe the behavior of electric and magnetic fields. Students will explore electromagnetic waves, their properties, and practical applications, including electric motors, inductive charging, etc.The second module covers relativity, starting with Einstein's postulates and the Lorentz transformations. Topics such as time dilation, length contraction, relativistic energy, and the curvature of spacetime will be examined, highlighting their relevance in technologies like GPS and particle accelerators.The third module introduces quantum mechanics, discussing foundational concepts such as wave-particle duality, the Schrödinger equation, quantum superposition, and tunneling effects. These principles are key to understanding nanoscale systems, quantum computing, and advanced materials like superconductors.The final module connects these concepts to real world applications, exploring how modern physics enables advancements in communication, material science, and energy systems. Topics include photonics in data transmission, graphene and superconductors in electronics, and nuclear physics in energy production and medical imaging.By the end of this course, students will develop a strong theoretical foundation in modern physics while gaining insight into its technological implications. Through a case study, they will learn to analyze and apply these principles to real world engineering challenges. Who this course is for Engineers, senior or grad students. Entrepreneurs and Innovators, designers, manufacturing professionals (with our without a college degree). Overall, Professionals Seeking Career Growth Homepage: https://www.udemy.com/course/physics-for-engineering-3-modern-physics/ Rapidgator https://rg.to/file/f670cf1ad1c32c5606757563c5d688a4/wpecp.Applied.Physics.For.Engineering.III.Modern.Physics.part1.rar.html https://rg.to/file/d41bd0a47ff3bc3bdeac6505686ea8de/wpecp.Applied.Physics.For.Engineering.III.Modern.Physics.part2.rar.html https://rg.to/file/e91456c79cf647a86ffccdc169dd6c1a/wpecp.Applied.Physics.For.Engineering.III.Modern.Physics.part3.rar.html Fikper Free Download https://fikper.com/y996ZzVXdL/wpecp.Applied.Physics.For.Engineering.III.Modern.Physics.part1.rar.html https://fikper.com/rSA4nb1ZkJ/wpecp.Applied.Physics.For.Engineering.III.Modern.Physics.part2.rar.html https://fikper.com/WXXWxScGUw/wpecp.Applied.Physics.For.Engineering.III.Modern.Physics.part3.rar.html No Password - Links are Interchangeable

Free Download From DevOps to Platform Engineering - Master Backstage & IDPs Published: 3/2025 Created by: Ricardo Andre Gonzalez Gomez MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 104 Lectures ( 9h 1m ) | Size: 4.6 GB Learn Backstage, Kubernetes, ArgoCD, Docker, GitHub Actions & CI/CD to build Internal Developer Platforms (IDPs). What you'll learn Gain a deep understanding of Platform Engineering and Internal Developer Portals (IDPs) Automate DevOps workflows using Backstage and Platform Engineering best practices Build, containerize, and deploy real-world applications from scratch Create a fully functional Internal Developer Platform (IDP) with Backstage Write and manage Documentation as Code using Backstage TechDocs Develop custom Backstage Software Templates to standardize application deployment Requirements Basic DevOps knowledge is helpful but not required - we'll cover the fundamentals A computer with at least 8GB RAM and 20GB of free disk space No prior Platform Engineering experience needed - perfect for beginners Description Are you a DevOps engineer looking to take your career to the next level? Are you curious about Platform Engineering and how Internal Developer Portals (IDPs) can revolutionize the way teams develop, deploy, and manage applications? If so, this course is designed for you!This course will take you from DevOps to Platform Engineering by mastering Backstage, an open-source framework developed by Spotify, and integrating it with modern DevOps tools to build a fully functional Internal Developer Platform (IDP).In this hands-on, project-based course, you will work on real-world DevOps projects, implementing automation and self-service workflows to streamline software delivery. By the end of this course, you will have gained practical experience in:Building and deploying applications using Docker, Kubernetes, and ArgoCDAutomating CI/CD pipelines with GitHub ActionsCreating an Internal Developer Platform (IDP) using BackstageWriting Documentation as Code with Backstage TechDocsImplementing Software Templates for faster application deploymentsDeploying Backstage in a production environmentThis course is practical, hands-on, and beginner-friendly, ensuring that you learn by doing rather than just theory. No prior Platform Engineering experience is required, but a basic understanding of DevOps, CI/CD, and infrastructure management will be beneficial.Join now and get ahead in the future of DevOps & Platform Engineering! Who this course is for DevOps Engineers looking to transition into Platform Engineering Cloud Engineers interested in self-service platforms and developer enablement Software & Infrastructure Engineers with a DevOps background who want to master Internal Developer Platforms (IDPs) Homepage: https://www.udemy.com/course/from-devops-to-platform-engineering-master-backstage-idps/ Rapidgator https://rg.to/file/09c996ac6705f17c913a7d15805f08c2/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part1.rar.html https://rg.to/file/b50bc078c664975ea6e0cb58257ba49f/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part2.rar.html https://rg.to/file/831979d40d652ff5fef14ed84ffad5de/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part3.rar.html https://rg.to/file/e08feb7f01789c81214aeebcecf423c8/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part4.rar.html https://rg.to/file/7b5928019b9133c5eb03130039b80300/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part5.rar.html Fikper Free Download https://fikper.com/7d0mRaxZpM/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part1.rar.html https://fikper.com/87TcJIaIiv/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part2.rar.html https://fikper.com/yWjEGi6T1p/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part3.rar.html https://fikper.com/E6cPHUlGsD/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part4.rar.html https://fikper.com/2ZoVvk7aAA/gvgrj.From.DevOps.to.Platform.Engineering.Master.Backstage..IDPs.part5.rar.html No Password - Links are Interchangeable

Free Download Ai Prompt Engineering And Tools For Marketing Businesses Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.25 GB | Duration: 5h 16m AI Prompt Engineering & Automation Tools: Revolutionizing Marketing Strategies for Businesses Using AI Chatbot What you'll learn AI Prompt Engineering Fundamentals AI Tools for Marketing & Automation AI Video & Image Creation for Marketing Generatve AI and prompt engineering AI tools for Marketer's How AI Works Requirements Basic understanding of marketing & content creation (Beginner-friendly) Willingness to learn AI-driven automation & tools No coding experience needed - 100% No-Code Approach! Access to AI tools (Free & Paid tools will be shared) Learn To Use AI Description Course Description: AI Prompt Engineering and Tools for Marketing BusinessesIn the era of AI-driven marketing, businesses must leverage AI prompt engineering and automation tools to stay ahead. This course, "AI Prompt Engineering & Automation Tools: Revolutionizing Marketing Strategies for Businesses Using AI Chatbots," provides a comprehensive guide to harnessing AI for marketing success.You'll learn how to craft effective AI prompts to optimize content creation, customer engagement, ad copywriting, email automation, and chatbot implementation. This course covers AI-powered tools like ChatGPT, Jasper, ManyChat, and Dialogflow to streamline business operations, enhance personalization, and increase conversions.Key Modules: Introduction to AI Prompt Engineering - Understanding AI models & prompt structures AI Chatbots for Business - Implementing ChatGPT-based chatbots for lead generation & support Marketing Automation with AI - Using AI for email, social media, and ad optimization Advanced Prompt Formulas - Crafting role-based, instructional, and contextual prompts Personalization & Customer Engagement - AI-driven interactions for higher retentionEmail Marketing with AI ToolsContent generating AI and SEO TOols By the end of this course, you'll be able to design AI-powered marketing campaigns, automate repetitive tasks, and enhance customer experience using cutting-edge AI tools. Who Should Enroll?Digital Marketers & EntrepreneursBusiness Owners & AgenciesContent Creators & FreelancersJoin now and unlock AI's full potential in marketing, automation, chabots and business success! Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Generative AI and How it Works Lecture 3 LLMs and Workflow Section 2: Prompt engineering and Structure Lecture 4 Prompt engineering Fundamental Lecture 5 Prompt Structure and Checklist Lecture 6 Generating Filtered Output with Structured prompt Lecture 7 Prompt errors Lecture 8 AI For Marketers Lecture 9 Email Marketing and Social Media Using AI Lecture 10 AI Tools Comparison on various Aspects Lecture 11 AI Chatbots Lecture 12 Advance AI Prompting Strategies Lecture 13 AI Tools and Implementation Section 3: AI Chatbots and Tools Lecture 14 AI Tools and AUTOMATION Lecture 15 AI Chatbots Lecture 16 Bonus Lecture Digital marketers & entrepreneurs,Freelancers & agency owners,Business owners looking for high-ROI ads,Content writers & seo writers,Any Graduate wanted to Learn AI & Auomation Homepage: https://www.udemy.com/course/ai-prompt-engineering-and-tools-for-marketing-businesses/ Rapidgator https://rg.to/file/71bb6f89f821f589f80cfeb8bb8e758a/kjuod.Ai.Prompt.Engineering.And.Tools.For.Marketing.Businesses.part1.rar.html https://rg.to/file/515b39344dc6dceabe7cc252726fbe10/kjuod.Ai.Prompt.Engineering.And.Tools.For.Marketing.Businesses.part2.rar.html https://rg.to/file/b8f5cd15d3114ec5a359a8d03b769c43/kjuod.Ai.Prompt.Engineering.And.Tools.For.Marketing.Businesses.part3.rar.html Fikper Free Download https://fikper.com/5GGl3PjNSj/kjuod.Ai.Prompt.Engineering.And.Tools.For.Marketing.Businesses.part1.rar.html https://fikper.com/bC9u0hwzrP/kjuod.Ai.Prompt.Engineering.And.Tools.For.Marketing.Businesses.part2.rar.html https://fikper.com/NhpqXl6bZQ/kjuod.Ai.Prompt.Engineering.And.Tools.For.Marketing.Businesses.part3.rar.html No Password - Links are Interchangeable

Free Download Data Engineering on AWS Vol 1 - OLAP & Data Warehouse Published: 1/2025 Created by: Soumyadeep Dey MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 212 Lectures ( 46h 3m ) | Size: 16.2 GB Detailed training (Level 350) on AWS Data Engineering Services Redshift, S3, Athena, Hive, Glue Catalog, Lakeformation What you'll learn Understand Data Engineering (Volume 1) on AWS using S3, Redshift, Athena and Hive Know Redshift, S3 and Athena up to Level 350+ with HANDS-ON Production level projects and hands-on to help candidates provide on-job-like training Get access to datasets of size 100 GB - 200 GB and practice using the same Learn Python for Data Engineering with HANDS-ON (Functions, Arguments, OOP (class, object, self), Modules, Packages, Multithreading, file handling etc. Learn SQL for Data Engineering with HANDS-ON (Database objects, CASE, Window Functions, CTE, CTAS, MERGE, Materialized View etc.) Requirements Good to have AWS and SQL knowledge Description This is Volume 1 of Data Engineering course on AWS. This course will give you detailed explanations on AWS Data Engineering Services like S3 (Simple Storage Service), Redshift, Athena, Hive, Glue Data Catalog, Lake Formation. This course delves into the data warehouse or consumption and storage layer of Data Engineering pipeline. In Volume 2, I will showcase Data Processing (Batch and Streaming) Services. You will get opportunities to do hands-on using large datasets (100 GB - 300 GB or more of data). Moreover, this course will provide you hands-on exercises that match with real-time scenarios like Redshift query performance tuning, streaming ingestion, Window functions, ACID transactions, COPY command, Distributed & Sort key, WLM, Row level and column level security, Athena partitioning, Athena WLM etc. Some other highlights:Contains training of data modelling - Normalization & ER Diagram for OLTP systems. Dimensional modelling for OLAP/DWH systems.Data modelling hands-on.Other technologies covered - EC2, EBS, VPC and IAM.This is Part 1 (Volume 1) of the full data engineering course. In Part 2 (Volume 2), I will be covering the following Topics.Spark (Batch and Stream processing using AWS EMR, AWS Glue ETL, GCP Dataproc)Kafka (on AWS & GCP)FlinkApache AirflowApache PinotAWS Kinesis and more. Who this course is for Data Engineers, Data Scientists, Data Analysts Python developers, Application Developers, Big Data Developers Database Administrators (DBA), Big Data Administrators Solutions Architect, Cloud Architect, Big Data Architect Technical Managers, Engineering Managers, Project Managers Homepage: https://www.udemy.com/course/data-engineering-vol-1-aws/ Rapidgator https://rg.to/file/9f1b4bf90979d93ea2eb5510b5d2405c/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part01.rar.html https://rg.to/file/b3248bce6be8f4e726f662e1d1815010/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part02.rar.html https://rg.to/file/17269bbbed85d0aea58028c11a84d3e8/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part03.rar.html https://rg.to/file/258fa67960dd4906cd42a41dd8dc83f0/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part04.rar.html https://rg.to/file/2b0fd5d5a54f50369e3fe17ac14a8b19/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part05.rar.html https://rg.to/file/d0f5482f42c64fe259019eaa77720d11/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part06.rar.html https://rg.to/file/27cff78ea02b54e0884b42969c212e8e/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part07.rar.html https://rg.to/file/2168de4a5190f36b63dcaa2c610c6967/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part08.rar.html https://rg.to/file/e2b74bd00149cd4b0ecf5d4828f08a6a/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part09.rar.html https://rg.to/file/2e286536532e3f5c7c86a279e81a4a3a/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part10.rar.html https://rg.to/file/bd18d7437266023341cc045e416987a9/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part11.rar.html https://rg.to/file/2cfbe9358d97fcc481c59e8a5dd9bf32/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part12.rar.html https://rg.to/file/332c5eb8f6c57f0acc8bb8c666ff44d0/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part13.rar.html https://rg.to/file/e1a13d910a8419a15cb614e996eb6904/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part14.rar.html https://rg.to/file/1b71cfc2d552e5bd09bf015ea6c05204/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part15.rar.html https://rg.to/file/26b463c8291f1326ba66bf4294b260a3/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part16.rar.html https://rg.to/file/790e86d71c54fc74132bbd289960c425/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part17.rar.html Fikper Free Download https://fikper.com/r17WWyft30/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part01.rar.html https://fikper.com/LlPcfG9zMc/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part02.rar.html https://fikper.com/1Ti1yo8T5S/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part03.rar.html https://fikper.com/vAYRDOOVaf/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part04.rar.html https://fikper.com/1mpbrbwaxr/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part05.rar.html https://fikper.com/fMHPzm0SqI/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part06.rar.html https://fikper.com/dMEPDnn3b4/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part07.rar.html https://fikper.com/Zpm4k6g6c3/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part08.rar.html https://fikper.com/eji8t6t0Zl/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part09.rar.html https://fikper.com/kTa1ACqbFU/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part10.rar.html https://fikper.com/bbteZGV5JL/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part11.rar.html https://fikper.com/293YkMBDbr/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part12.rar.html https://fikper.com/uCOV7YONOb/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part13.rar.html https://fikper.com/lxL26W4Ywt/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part14.rar.html https://fikper.com/qS5I9cs6ch/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part15.rar.html https://fikper.com/ja2yCv1Hla/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part16.rar.html https://fikper.com/V6WqeVmdxb/olrzy.Data.Engineering.on.AWS.Vol.1..OLAP..Data.Warehouse.part17.rar.html No Password - Links are Interchangeable

Free Download AI Engineering Use Cases and Projects on AWS - Production-Grade LLM Systems Released: 03/2025 Duration: 46m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 90 MB Level: Intermediate | Genre: eLearning | Language: English Discover the intricate architecture of production-level large language models (LLMs) using Rust on AWS. Instructor Noah Gift covers an array of key topics, including the Ollama DeepSeek-R1, Claude, and other cutting-edge LLM systems, as well as open-source strategies and multimodel workflows. Along the way, get hands-on experience with YAML prompts and proxy routing to optimize your language models. Designed for AI engineers, developers, and tech enthusiasts, this course provides the skills necessary to advance your expertise in AI and machine learning. By the end of this course, you'll be prepared to deploy and scale sophisticated language models in a production-grade environment, staying ahead of the curve in the rapidly evolving field of AI. This course was Created by: Noah Gift and Pragmatic AI Labs. We are pleased to host this training in your library. Homepage: https://www.linkedin.com/learning/ai-engineering-use-cases-and-projects-on-aws-production-grade-llm-systems Fileaxa https://fileaxa.com/tsqy3f3x06nx/sguxi.Linkedin..AI.Engineering.Use.Cases.and.Projects.on.AWS.ProductionGrade.LLM.Systems.rar TakeFile https://takefile.link/hvos6wxh0bba/sguxi.Linkedin..AI.Engineering.Use.Cases.and.Projects.on.AWS.ProductionGrade.LLM.Systems.rar.html Rapidgator https://rg.to/file/b8037c1ef3918c68d87e54fb83259e34/sguxi.Linkedin..AI.Engineering.Use.Cases.and.Projects.on.AWS.ProductionGrade.LLM.Systems.rar.html Fikper Free Download https://fikper.com/HNk7RHoKQ8/sguxi.Linkedin..AI.Engineering.Use.Cases.and.Projects.on.AWS.ProductionGrade.LLM.Systems.rar.html No Password - Links are Interchangeable

Free Download Udemy - Prompt Engineering and AI Literacy Masterclass Published: 3/2025 Created by: Chris Lele MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 31 Lectures ( 3h 58m ) | Size: 3.45 GB Master AI prompting and boost productivity with expert techniques for ChatGPT, Claude, & Gemini. What you'll learn Use Generative AI to its fullest. Optimize for use cases that are important to you. Develop unique and practical ways of thinking about prompting and LLMs. Outperform those who only think in terms of prompt engineering. Know when and when not to use Generative AI. Use Generative AI in novel and fun ways. Requirements Access to ChatGPT and/or other popular LLMs. Description This is your complete course on Prompt Engineering and AI Literacy. Prepare to master Generative AI tools like ChatGPT, Claude, and Gemini. Whether you're a business professional, content creator, educator, or simply curious about AI, this course will teach you how to think about prompting and craft effective prompts that maximize AI's capabilities and enhance your productivity at work, school, or in your daily life! We'll go beyond just teaching you premade prompts and really help you develop innovative ways of thinking about prompting and LLMs.Designed for anyone who wants to master the principles of prompt engineering, and refine their queries to get more precise, useful, and insightful responses. You'll explore key techniques that improve AI's performance in writing, research, analysis, and brainstorming. We'll show you six Golden Rules of prompting that will take your LLM outputs from generic to exceptional!Beyond just crafting better prompts, we'll also dive into AI literacy, helping you to recognize the strengths and limitations of AI models. We'll show you how to use AI ethically and effectively in professional and personal settings.By the end of this course, you'll be equipped with the skills you need to confidently work with AI-powered tools, enhance your workflows, and leverage AI as a powerful thought partner. Join us and take your AI skills to new heights! Who this course is for This course is professionals, students, or curious-minded individuals who want to take their AI prompting skills to new heights. Homepage: https://www.udemy.com/course/prompt-engineering-and-ai-literacy-masterclass/ Rapidgator https://rg.to/file/982c84dafb96e1829ab65f4580d7ad5f/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part1.rar.html https://rg.to/file/39f3cd55507d6a9d9dd542605f8a3066/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part2.rar.html https://rg.to/file/e52e8ce30e1f55713d12445ddae603d5/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part3.rar.html https://rg.to/file/4a445705d53cb216f4d97800454b3e77/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part4.rar.html Fikper Free Download https://fikper.com/0xJffHl8Hz/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part1.rar.html https://fikper.com/ZdgiYwDeud/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part2.rar.html https://fikper.com/nE3evQ36n8/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part3.rar.html https://fikper.com/YoAfANfwSF/ngjtt.Prompt.Engineering.and.AI.Literacy.Masterclass.part4.rar.html No Password - Links are Interchangeable

Free Download Udemy - Engineering & Data Science Essentials Published: 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 56m | Size: 248 MB Master data analysis, visualization, and decision-making for real-world engineering challenges. What you'll learn The fundamentals of engineering principles and how they relate to data science Data analysis techniques to extract valuable insights from data How to use data visualization tools to communicate complex information effectively Problem-solving strategies for engineering and technical challenges How to apply data-driven decision-making in real-world scenarios Requirements No prior data science experience required - We cover the fundamentals. Basic understanding of engineering or mathematics is helpful but not mandatory. A willingness to analyze and interpret data using real-world case studies. Access to a computer with internet for hands-on exercises and visualization tools. Description In today's fast-paced world, engineers and data scientists must work together to solve complex problems using data-driven insights. This course bridges the gap between engineering fundamentals and data science, equipping you with the analytical and problem-solving skills needed to thrive in industries like technology, manufacturing, and research.Through hands-on lessons, real-world case studies, and practical tools, you will learn to analyze data, visualize insights, and apply engineering principles to make strategic decisions. Whether you're an engineer looking to expand into data science or a data enthusiast aiming to understand engineering applications, this course is designed for you.What makes this course different?Comprehensive Curriculum - Covers engineering fundamentals, data analysis, visualization, and decision-making techniques.Real-World Applications - Learn how data science is transforming industries with practical case studies.Hands-On Learning - Gain experience with problem-solving techniques and data visualization tools.What you will learn: The fundamentals of engineering principles and how they relate to data science Data analysis techniques to extract valuable insights from data How to use data visualization tools to communicate complex information effectively Problem-solving strategies for engineering and technical challenges How to apply data-driven decision-making in real-world scenariosWho Is This Course For?Engineers looking to enhance their data science skillsData scientists interested in applying their skills to engineering problemsStudents & professionals in STEM fields wanting a practical approach to data analysisManagers & decision-makers who need data-driven insights for strategic planningInstructor Bio:Taught by Sam, an experienced engineer and data scientist, this course is designed with practical industry applications in mind. With over 3 years of experience, Sam has worked on cutting-edge projects, helping businesses leverage data for smarter decisions. Enroll now and start mastering data-driven engineering strategies today! Who this course is for Engineers looking to enhance their data science skills Data scientists interested in applying their skills to engineering problems Students & professionals in STEM fields wanting a practical approach to data analysis Managers & decision-makers who need data-driven insights for strategic planning This course is designed to be beginner-friendly, making it easy for anyone interested in engineering and data science to get started! Homepage: https://www.udemy.com/course/engineering-data-science-essentials/ Rapidgator https://rg.to/file/1eeb26f0ebbb4b5d3550bb3d18ea866c/ffzzf.Engineering..Data.Science.Essentials.rar.html Fikper Free Download https://fikper.com/pxVwLCL9oP/ffzzf.Engineering..Data.Science.Essentials.rar.html No Password - Links are Interchangeable

Free Download Udemy - Engineering the Job Search Published: 3/2025 Created by: Farah Bajwa MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 61 Lectures ( 3h 48m ) | Size: 1.2 GB Landing that dream job by becoming the choice candidate What you'll learn Identifying your target job in your target industry Networking: accessing the "Hidden Job Market", how/where to network, elevator pitches, imposter syndrome, scams The ATS (Applicant Tracking System): significance and how to hack it Cover Letters: when to write them and what to include Resumes: the different types, key sections, strategies on how to write them, hiring manger red flags Applications: guidelines during and after, red flags Interviews: types, etiquette, prep for online and in-person, post-interview steps, questions they can ask you, questions you can ask them Thank you Notes: importance, methods, what to include Following Up: timing, method, what to include, ghosting Managing Expectations: emotions, experimentation Requirements All you need is a desire to learn how to stand out as the Engineer of Choice Description I once said to a STEM headhunter that "engineers are capable of making career decisions for themselves". She gave me a pained look that told me she was biting her tongue. This fueled my drive to build this course. If we're intelligent enough to send people to the moon and conceive life-saving medical devices, we are more than capable of designing our own careers. We all want to be on a career path that's enjoyable and fulfilling, because the more you enjoy your work, the less it'll feel like work, right? That starts by equipping ourselves with knowledge and this is your on stop shop. I provide you with every iota of information I have, including my own personal notes and examples. I share everything, telling you whether I agree with it or not, and what has personally worked for me.You'll walk out of this course knowing the ins and outs of the job search process and hacking strategies to stand out as the candidate of choice - the Engineer of Choice; Thereby optimizing your candidacy to land your dream or preferred position or internship in Engineering.Along with the hand-outs, this course includes:The course cheat sheetAn ATS-friendly resume templateAI/Chat GPT promptsQuestions the interviewers may ask youMy personal list of questions I ask my interviewersAnd, to ensure you know where to go from there, I'm including some Add-on material: Time Management AdviceHandling Rejection, Offer Acceptance, and ResignationNegotiation Tips Who this course is for Engineers who want to optimize their chances of landing their dream job Those entering the engineering work force who want to optimize their chances of landing their dream job Students applying for internships Homepage: https://www.udemy.com/course/engineering-the-job-search/ Rapidgator https://rg.to/file/2c0224d1b712a7b447d98398b390e732/wgpmz.Engineering.the.Job.Search.part1.rar.html https://rg.to/file/ccc7fc6c34c6c6a1f7b1fd8a70f61184/wgpmz.Engineering.the.Job.Search.part2.rar.html Fikper Free Download https://fikper.com/2IzMMTzXB9/wgpmz.Engineering.the.Job.Search.part1.rar.html https://fikper.com/n1qUPBEpDP/wgpmz.Engineering.the.Job.Search.part2.rar.html : No Password - Links are Interchangeable

Free Download Rust Data Engineering and Analytics - Production Ready 2025 Published: 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 10m | Size: 641 MB Rust Data Engineering / Analytics - Automated Pipelines Ready for Production with Docker and Elusion library What you'll learn Data Engineering and Data Analysis Data Wrangling with DataFrame API Functions Query OPTIMIZATION with VIEWS and CACHING REST API, Azure BLOB storage Pipeline Scheduling Production Depoloyment with Docker Requirements No experience nor Rust knowledge needed Basic SQL and DataFrame knowledge needed Description Level Up Your Data Game: Build Production-Ready Pipelines with RustIn this course you will learn how to create Automated Data Engineering / Analytics Pipeline that is ready to be pushed into production. You will learn how to use the most feature rich Rust DataFrame library - Elusion - to accomplish data cleaning, aggregations, pivoting and more...Tired of clunky data pipelines? Get ready to supercharge your data engineering skills with Rust's most powerful DataFrame library!What You'll Master:Lightning-fast data processing with ElusionProfessional-grade data cleaning techniquesAdvanced aggregations that reveal hidden insightsDynamic pivoting that transforms your analysisProduction-ready pipeline architecture that scalesWhy This Course Matters:The demand for efficient, reliable data pipelines has never been higher. While Python solutions struggle with performance bottlenecks, Rust offers unprecedented speed and memory safety. Elusion brings the power of Rust to data engineering, enabling you to build systems that process millions of rows in seconds.Course Highlights:Real-world Projects: Apply your skills to industry-relevant challengesPerformance Optimization: Learn how to squeeze every ounce of performance from your data operationsError Handling: Build robust pipelines that gracefully manage exceptionsDeployment Strategies: Master CI/CD integration for your data workflowsMonitoring & Maintenance: Implement logging and alerting to keep your pipelines healthyWho Should Attend:Whether you're a data engineer looking to level up your toolkit, a software developer curious about data processing, or a data scientist tired of waiting for analyses to complete, this course will transform how you work with data.Stop wrestling with inefficient tools. Join us and build blazing-fast, rock-solid data pipelines that are ready for the real world from day one.Elusion + Your Skills = Data Engineering Mastery Who this course is for Data Engineers and Data Analysts Rust Beginners Homepage: https://www.udemy.com/course/rust-data-engineering-analytics-elusion/ Rapidgator https://rg.to/file/174cd27cf7c0a5c3b60ac4bf0aae3dcb/svzfd.Rust.Data.Engineering.and.Analytics..Production.Ready.2025.rar.html Fikper Free Download https://fikper.com/z7nIssUUVq/svzfd.Rust.Data.Engineering.and.Analytics..Production.Ready.2025.rar.html : No Password - Links are Interchangeable

Free Download Udemy - Choosing Engineering Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 167.40 MB | Duration: 0h 40m Is an Engineering Career Path right for you (and are you right for engineering)? What you'll learn Is engineering for me? How do I choose which engineering role is best suited for my personality? What skills do I need? Do I have to be a problem solver? What is a good plan to become an engineer? What are some areas of study within engineering? How do the engineering programs at various schools/universities differ and why does it matter? Do I need to be good at math and physics? What industries can I work in? What is a Project Life Cycle and how does it relate to my future in engineering? What engineering disciplines can I work as? What factors go into deciding on the most suitable discipline for me? As an engineer, can I work remotely? Requirements This course will save you time, effort, and money - you'll walk out of class knowing how to make an informed decision on whether an engineering career is the best choice for you, and how to plan for the most ideal path in it. Description Choosing Engineering is about the info they don't teach in school. It's meant to help you evaluate and decide if engineering is something you should consider pursuing or not from a more practical perspective.Knowing what to expect and what to plan for will help you more effectively and efficiently map out your career. So I've put into this course everything I really wish someone would have shared with me when I had first expressed an interest in studying engineering and in an engineering career. Compiling decades of experience and lessons learned from myself and others, I create this structured, one-of-a-kind course to guide you through the different key elements you should consider without having to figure it all out on your own the hard way through real-life trial and error. And so that you can go through the material at your own pace and rewatch what you need.And to help you figure out where to go after you complete the course, at the end I throw in an Add-on section:Now that I know all of this, where do I go from here? What are some next steps to take?What's a PE license? How do I obtain it? Overview Section 1: Choosing Engineering Introduction Lecture 1 Preparing to Begin/Setting Up for Success Lecture 2 Choosing Engineering Intro Lecture 3 Course Agenda Section 2: Things to Ask Yourself Lecture 4 Why Do I want to be an Engineer? Lecture 5 Is Engineering for Me? Lecture 6 How do I become that Engineer? Section 3: Making Choices Lecture 7 Choosing the Area of Study Lecture 8 Choosing the University/College Lecture 9 Choosing the Lifestyle Section 4: Breaking Out the Lifestyle Lecture 10 Choosing the Industry Lecture 11 Industry Examples Lecture 12 A Quick Heads Up Lecture 13 Project Life Cycle Lecture 14 Choosing the Discipline Lecture 15 Discipline Examples Lecture 16 Knowing Yourself Section 5: Choosing Engineering Wrap Up Lecture 17 Wrap Up Section 6: Add-on: Next Steps and Extra Material Lecture 18 Next Steps Lecture 19 Professional Engineer License Lecture 20 Summary Students thinking about making engineering their career path,Anyone considering a career change and is wondering if engineering is right for them Homepage: https://www.udemy.com/course/choosing-engineering/ DOWNLOAD NOW: Udemy - Choosing Engineering Rapidgator https://rg.to/file/33f5e2720ea752240a4a6226ecb0070e/umjio.Choosing.Engineering.rar.html Fikper Free Download https://fikper.com/E0CtGrHgaH/umjio.Choosing.Engineering.rar.html : No Password - Links are Interchangeable

Free Download Udemy - Pivoting Engineering Published: 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 14m | Size: 451 MB Identify the Intentional Next Move in Your Career What you'll learn Identify the most ideal role for your personality using the Brainstorm and Prioritization exercises Identify the most ideal industry for your personality using the Brainstorm and Prioritization exercises Discover interesting truths about where you are and where you want to be How to bridge the gaps to get to where you want to be Requirements No Requirements expect to be honest with yourself when answering the question sin the exercises we do together. The more honest you are with yourself the more accurate your results. And the more likely you'll be at the start of a path to something more fulfilling. Description After I graduated with a customized Engineering Degree (I'll explain later) and took on my first engineering job, I thought I was going to stay with that company forever.I was wrong.That's no longer how the corporate world works. Most companies are now "at will" in letting employees go. Also, as my experience grew, I found that my interests were changing.Those realizations made me start exploring how to make active changes in my career rather than waiting for things to happen for me.Whether you're a recent grad with a little work experience, or an engineer with decades of experience, this course will teach you the strategy I used to successfully PIVOT my Engineering career. We will walk through the Brainstorm and Prioritization exercises together. And you'll walk out of class with the new role/industry you should focus your energy and efforts on. Or, you'll walk out knowing that its time to leave the engineering world.This strategy works. I've gone through the process myself and have helped many others!Then, to ensure you know where to go from there, I'm including some Add-on material:Some next steps to takeResume TipsCover Letter ImportancePE License InformationNote: To be clear, this pivoting course is about identifying the most ideal role/industry for you personally (or confirming your compatibility with the one you already have in mind), and identifying what's standing in the way of obtaining it. This course is not about the job hunting process. Who this course is for Any engineer feeling stuck in their career or is wanting to make a change, or pivot. Homepage: https://www.udemy.com/course/pivoting-engineering/ DOWNLOAD NOW: Udemy - Pivoting Engineering Rapidgator https://rg.to/file/5d28f85bfbee5fd37139cb714dc440b8/ipwpf.Pivoting.Engineering.rar.html Fikper Free Download https://fikper.com/W4kEMSVnCx/ipwpf.Pivoting.Engineering.rar.html : No Password - Links are Interchangeable

Free Download ZerotoMastery - AI Engineering Bootcamp Retrieval Augmented Generation (RAG) for LLMs Released 2/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 150 Lessons ( 17h 53m ) | Size: 4.8 GB Learn to make smarter AI systems by combining LLMs with Retrieval-Augmented Generation (RAG). Build real-world projects using RAG architecture including chatbots, financial analysis tools, and much more! What you'll learn Combine generative AI models with Retrieval Augmented Generation to build smarter AI systems Use OpenAI APIs for text generation and processing unstructured data Master FAISS for efficient similarity searches in massive datasets Apply prompt engineering techniques for optimal AI responses Build real-world AI projects like chatbots and financial analysis tools Explore advanced RAG concepts like multimodal and agentic RAG What Is An AI Engineer? The short version is that an AI Engineer works on the entire lifecycle of an AI application - that is, an application that utilizes AI at its core. An AI Engineer takes AI models, including Large Language Models, and customizes them to their needs. (If you want the long version, check out our blog post here) That requires everything from building models using custom datasets, to training and tuning models, to deploying models and scaling them using cloud technologies. The role is growing like wildfire, but it's still evolving and will no doubt continue evolving as the AI landscape changes. What Is Retrieval Augmented Generation (RAG)? Have you ever wondered why some AI systems can feel limited, giving answers that seem a bit generic or off-target? Well that's because they're limited to the knowledge in their training data. And that's a lot of data. But it's not everything. It doesn't include private data, nor does it include recent data that has been created since the model was trained. Retrieval-Augmented Generation, or RAG, addresses this by supplementing AI models with that private or new information. Instead of relying only on what it was trained on, RAG retrieves up-to-date, relevant information from a database or document. Here's how it works: the system first finds the most relevant pieces of information for a given question (retrieval). Then, it uses a language model to generate a response based on that information (generation). That's why it's called retrieval-augmented generation! The result is an AI that combines the best of both worlds: real-time access to external knowledge and the ability to express it clearly. Let's do an example. Picture this: You're browsing a clothing store's website, looking for a specific jacket in your size and favorite color, but you're not sure if it's in stock. Instead of clicking through endless filters, a chatbot powered by RAG can make this effortless. When you ask, "Do you have the blue jacket in a medium size?" the RAG system retrieves real-time inventory data from the store's database. It finds the exact details, like availability in nearby stores or estimated delivery dates - information that would not be in the AI model's training data. And then it uses that information to generate a useful response: "Yes, we have it in stock! You can pick it up at our downtown location or have it delivered by Friday." This kind of dynamic, accurate interaction makes shopping easier and faster, ensuring you get the answers you need without the hassle. RAG is increasingly used in AI applications like chatbots, research tools, and data analysis systems, where accuracy and context are essential. It's a practical way to make AI more reliable and useful in complex scenarios. Why This RAG Course? Well, because it's the best, most up-to-date, and practical AI Engineering Bootcamp course online that teaches you real-world RAG skills and that lets you get hands-on so that you can actually use your skills in the real-world. But of course we're biased. So here's a breakdown of what's covered in this RAG Bootcamp course so that you can make up your own mind 1. Basics of Retrieval Systems: This section lays the foundation for understanding how to search and retrieve information from large datasets. You will learn how to prepare text data for retrieval, explore different retrieval models (Boolean, vector space, probabilistic), and understand the concepts of indexing, querying, and ranking. The goal is to equip you with the skills to efficiently find relevant information within massive datasets. 2. Basics of Generation Models: Building on the retrieval concepts, this section introduces the principles of text generation using AI. You will learn about the transformer architecture, which has revolutionised natural language processing, and how attention mechanisms within transformers allow models to focus on the most relevant parts of the input. You will also gain an understanding of data preparation and training techniques for these models. 3. Introduction to RAG: This section introduces the core concepts of Retrieval-Augmented Generation, explaining how it combines the strengths of retrieval and generation models to create more accurate, contextually relevant, and comprehensive responses. You will learn about the basic RAG architecture and understand why it is becoming increasingly important in various AI applications. 4. Working With The OpenAI API: This section focuses on teaching you how to use OpenAI's API for accessing and utilizing their powerful AI models, particularly for text generation and image processing. You will learn about obtaining API keys, setting up your environment, crafting effective prompts, tuning parameters, and understanding the system prompt's influence on the AI's behaviour. 5. RAG with OpenAI Implementation: This section brings together everything you have learned so far to teach you how to build fully functional RAG systems using OpenAI models. You will integrate retrieval and generation components, explore advanced RAG concepts like multi-modal RAG, and use the OpenAI API to create intelligent systems capable of handling complex tasks. 6. Working with Unstructured Data: This section delves into the challenges and techniques for working with unstructured data, which constitutes a vast majority of real-world information. You will learn how to process and extract information from various formats like PDFs, Word documents, PowerPoint presentations, EPUBs, images, and Excel data. This section equips you with the tools to unlock the value hidden within unstructured data. 7. Multimodal RAG: Building on your understanding of RAG, this section introduces the concept of multi-modal RAG, which extends the capabilities of RAG to handle data from multiple modalities, such as text and images. You will learn how to build systems that can integrate different data types to generate richer and more contextually relevant responses. 8. Agentic RAG: This section introduces the concept of agentic RAG, focusing on building AI agents that can interact with users, handle tasks, and make decisions autonomously. The course covers agent state management, workflows, and integrating retrieval and generation into agentic systems. This section represents the cutting edge of RAG development and explores how AI agents can dynamically respond to user requests and complete complex tasks. Homepage: https://zerotomastery.io/courses/ai-engineer-bootcamp-retrieval-augmented-generation/ DOWNLOAD NOW: ZerotoMastery - AI Engineering Bootcamp Retrieval Augmented Generation (RAG) for LLMs Fileaxa https://fileaxa.com/aprbk8h9i4ef/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part1.rar https://fileaxa.com/zg6dk941nl48/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part2.rar https://fileaxa.com/dkfpu2c8a9hy/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part3.rar https://fileaxa.com/wgk2wnpgmqsk/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part4.rar https://fileaxa.com/urdyrspuklpg/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part5.rar TakeFile https://takefile.link/8np4xr80cf5i/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part1.rar.html https://takefile.link/yqd5gmypgaa8/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part2.rar.html https://takefile.link/2uggeuffe07p/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part3.rar.html https://takefile.link/ktqlzsxnrrda/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part4.rar.html https://takefile.link/y7r0358njq88/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part5.rar.html Rapidgator https://rg.to/file/c548f90f64d94c25c136e5b8f8b71686/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part1.rar.html https://rg.to/file/b546d628b996111d37f26041ae28b7ed/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part2.rar.html https://rg.to/file/7a0cd7ef4e06fa5c432fe2c6eb70aeed/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part3.rar.html https://rg.to/file/a9ef30fe141937c414ef1984baa6ada5/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part4.rar.html https://rg.to/file/a1b3b8b88e6c0d7ed04a9abb43c80db3/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part5.rar.html Fikper Free Download https://fikper.com/gkKmqmId1n/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part1.rar.html https://fikper.com/PbN5wDB31w/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part2.rar.html https://fikper.com/75L9qaPsX0/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part3.rar.html https://fikper.com/CkMjQ0Zsz8/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part4.rar.html https://fikper.com/OMXxQ8JpqL/wnhjt.ZerotoMastery..AI.Engineering.Bootcamp.Retrieval.Augmented.Generation.RAG.for.LLMs.part5.rar.html : No Password - Links are Interchangeable

Free Download Udemy - Automotive System Engineering In Aspice Perspective Published: 2/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.13 GB | Duration: 1h 24m Automotive System Engineering in ASPICE Perspective ; Detailed explaination of the System development in various stages What you'll learn ASPICE SYSTEM Engineering From SYS.1 to SYS.5 System Engineers Automotive Students Requirements Basic Automobile knowledge, Any automobile/Automotive Enthusisast Description Automotive Systems Engineering (ASE) plays a crucial role in the development of modern vehicles, ensuring safety, reliability, and efficiency. With the increasing complexity of automotive electronics, software, and hardware integration, the industry has adopted rigorous frameworks like Automotive SPICE (ASPICE) to standardize and improve development processes. ASPICE, or Automotive Software Process Improvement and Capability dEtermination, provides a structured approach to assessing and enhancing the maturity of software and system engineering activities within automotive projects.From an ASPICE perspective, Automotive Systems Engineering is not just about designing components but involves a systematic approach to managing Requirements, architecture, design, integration, verification, and validation. It ensures that software, hardware, and mechanical elements work seamlessly together in a vehicle. ASPICE categorizes system development into key processes, such as System Requirements Analysis (SYS.2), System Architectural Design (SYS.3), and System Integration & Testing (SYS.4 & SYS.5). These processes ensure a clear breakdown of Requirements, a well-defined architecture, and robust integration and testing practices.Implementing ASPICE in Automotive Systems Engineering helps manufacturers and suppliers achieve higher product quality, functional safety compliance (ISO 26262), and cybersecurity robustness (ISO/SAE 21434). As vehicles become more software-driven, ASPICE-aligned systems engineering ensures consistent development methodologies, reducing risks and improving overall project success. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Lecture 2 Lecture 3 Lecture 3 Lecture 4 lecture 4 Lecture 5 lecture 5 Lecture 6 lecture 6 Lecture 7 Lecture 7 Any one interested in ASPICE and System Engineering Homepage: https://www.udemy.com/course/automotive-system-engineering-in-aspice-perspective/ DOWNLOAD NOW: Udemy - Automotive System Engineering In Aspice Perspective Rapidgator https://rg.to/file/814e0aa73a0682f0017606f27a1a1e0e/opfez.Automotive.System.Engineering.In.Aspice.Perspective.part1.rar.html https://rg.to/file/c88f55f0452f6bfae176e56a60db7cb3/opfez.Automotive.System.Engineering.In.Aspice.Perspective.part2.rar.html Fikper Free Download https://fikper.com/wCaE5YUxbI/opfez.Automotive.System.Engineering.In.Aspice.Perspective.part1.rar.html https://fikper.com/afD1VFogAW/opfez.Automotive.System.Engineering.In.Aspice.Perspective.part2.rar.html : No Password - Links are Interchangeable

pdf | 30.13 MB | English| Isbn:3540292497 | Author: Price, David George | Year: 2008 Description: Category:Science & Technology, Engineering, Earth Science, Energy & Power Resources, Geology, Geology - Mining & Engineering, Petroleum Technology - General & Miscellaneous TurboBit RapidGator https://rapidgator.net/file/f4422adfe45472cb26ad1bba105131d1/Engineering.Geology.-.Principles.and.Practice.rar AlfaFile https://alfafile.net/file/AStuU/Engineering.Geology.-.Principles.and.Practice.rar https://turbobit.net/0yxglp9sdpf6/Engineering.Geology.-.Principles.and.Practice.rar.html

Free Download Ai & Llm Engineering Mastery - Genai, Rag Complete Guide Published: 2/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 16.21 GB | Duration: 28h 11m From Fundamentals to Advanced AI Engineering - Fine-Tuning, RAG, AI Agents, Vector Databases & Real-World Projects What you'll learn Master the architecture and workflow of a RAG system for processing PDFs and multimodal data. Master the Fundamentals of AI, Machine Learning and Deep Learning (Basics) Master LangChain tools, frameworks, and workflows, including embedding techniques and retrievers. Fine-tuning models with OpenAI, LoRA, and other techniques to customize AI responses. Develop AI-driven applications with advanced RAG techniques, multimodal search, and AI agents for real-world use cases. Requirements Basics of Programming - Python Fundamentals INCLUDED Description Become an AI Engineer and master Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, and vector databases in this comprehensive hands-on course. Whether a beginner or an experienced developer, this course will take you from zero to hero in building real-world AI-powered applications.This course combines deep theoretical insights with hands-on projects, ensuring you understand AI model architectures, development and optimization strategies, and practical applications.What You'll Learn:Deep Learning & Machine Learning FoundationsUnderstand neural networks, activation functions, transformers, and the evolution of AI.Learn how modern AI models are trained, optimized, and deployed in real-world applications.Master Large Language Models (LLMs) & Transformer-Based AIDeep dive into OpenAI models, and open-source AI frameworks.Build and deploy custom LLM-powered applications from scratch.Retrieval-Augmented Generation (RAG) & AI-Powered SearchLearn how AI retrieves knowledge using vector embeddings, FAISS, and ChromaDB.Implement scalable RAG systems for AI-powered document search and retrieval.LangChain & AI Agent WorkflowsBuild AI agents that autonomously retrieve, process, and generate information.Fine-Tuning LLMs & Open-Source AI ModelsFine-tune OpenAI, and LoRA models for custom applications.Learn how to optimize LLMs for better accuracy, efficiency, and scalability.Vector Databases & AI-Driven Knowledge RetrievalWork with FAISS, ChromaDB, and vector-based AI search workflows.Develop AI systems that retrieve and process structured & unstructured data.Hands-on with AI Deployment & Real-World ApplicationsBuild AI-powered chatbots, multimodal RAG applications, and AI automation tools.Who Should Take This Course?Aspiring AI Engineers & Data Scientists - Looking to master LLMs, AI retrieval, and search systems.Developers & Software Engineers - Who want to integrate AI into their applications.Machine Learning Enthusiasts - Seeking a deep dive into AI, GenAI, and AI-powered search.Tech Entrepreneurs & Product Managers - Wanting to build AI-driven SaaS products.Students & AI Beginners - Who need a structured, step-by-step path from beginner to expert.Course RequirementsNo prior AI experience required - the course takes you from beginner to expert.Basic Python knowledge (recommended but not required - Python Fundamentals Included in the course).Familiarity with APIs & JSON is helpful but not mandatory.A computer with internet access for hands-on development.Why Take This Course?Comprehensive AI Training: Covers LLMs, RAG, AI Agents, Vector Databases, Fine-Tuning.Hands-On Projects: Every concept is reinforced with real-world AI applications.Up-to-Date & Practical: Learn cutting-edge AI techniques & tools used in top tech companies.Zero to Hero Approach: Designed for absolute beginners & experienced developers alike.Master AI Engineering and become an expert in GenAI, LLMs, and RAG today. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 DEMO - What You'll Build in this Course Lecture 3 Course Structure Lecture 4 How To Get The Most from This Course Section 2: Development Environment Setup Lecture 5 Development Environment Setup - Overview Lecture 6 Install Python on Windows - for WINDOWS USERS Lecture 7 Install Python on MAC - for MAC USERS Lecture 8 Download Visual Studio Code Lecture 9 Install the Python Extension Pack for VS Code Lecture 10 Running First Python Program in VS Code Section 3: Do You Know Python? Lecture 11 Python Deep Dive - Introduction and Overview Section 4: OPTIONAL - Python Deep Dive - Master Python Fundamentals Lecture 12 What is Python and Where It's Used? Lecture 13 Python Compilation & Interpretation Process Lecture 14 Download Python Fundamentals Code Lecture 15 Declaring Variables in Python Lecture 16 Data Types Lecture 17 Python f-Strings Lecture 18 Numbers - Integers and Floats Lecture 19 Introduction to Lists - Accessing and Modifying Them Lecture 20 f-Strings & Individual Values from a List Lecture 21 Sorting a List and Getting a List Length Lecture 22 Lists and Loops - Looping through a List Lecture 23 Making a List of Numbers with Loops and the Range Function Lecture 24 Statistics Functions for Numbers Lecture 25 Generate Even Numbers with the List and Range Lecture 26 Important: Code Organization Note Lecture 27 List Comprehension Lecture 28 Tuples Lecture 29 Branching - If Statements and Booleans Lecture 30 The Elif and the in Keywords Lecture 31 Hands-on - Using AND and OR Logical Operators Lecture 32 AND OR Logical Operators Lecture 33 Checking for Inequalities Lecture 34 Hands-on - Inner If-Statements Lecture 35 Data Structures - Dictionaries - Introduction and Declaring and Accessing Values Lecture 36 Modifying a Dictionary Lecture 37 Iterating Through a Dictionary Lecture 38 Nested Dictionaries and Looping Through Them Lecture 39 Looping through a Dictionary with a List Inside Lecture 40 User Input and While Loops - User Input - Introduction Lecture 41 Hands-on - Odd or Even Number Lecture 42 While Loops & Simple Quit Program Lecture 43 Hands-on - Quiz Game Lecture 44 Removing all Instances of Specific Values from a List Lecture 45 Hands-on Dream Travel Itinerary Program - Filling a Dictionary with User Input Lecture 46 Functions - Introduction Lecture 47 Passing Information to a Function (parameters) Lecture 48 Positional and Named Arguments Lecture 49 Default Values - Parameters Lecture 50 Return Values from a Function Lecture 51 Hands-on - Returning an Integer & Intro do DocString Lecture 52 Functions - Passing a List as Argument Lecture 53 Passing an Arbitrary Number of Arguments to a Function Lecture 54 Introduction to Modules - Importing Specific functions from a Module Lecture 55 Using the "as" as an Alias Lecture 56 Classes and OOP - Object Oriented Programming - The "init and "str" methods Lecture 57 Adding More Methods to the Class Lecture 58 Setting a Default Value for an Attribute Lecture 59 Modifying Class Attribute - directly and with Methods Lecture 60 Inheritance - Create an Ebook - Child Class Lecture 61 Overriding Methods Lecture 62 Creating and Importing from a Module Lecture 63 The Object Class - Overview Lecture 64 The Python Standard Library Lecture 65 Random Module - Random Fruit Hands-on Lecture 66 Hands-on - Random Fruit with Choice Module Method Lecture 67 Using Datetime Module Lecture 68 Writing & Reading Files - Do Useful Tasks with Python - Do amazing things Lecture 69 The Path Class & Reading a Text File Lecture 70 Resolving Path - Reading From a Subdirectory with Path Lecture 71 Path Properties Overview Lecture 72 Writing to Text file with Path Lecture 73 Read and Write to File Using the "with" Keyword Lecture 74 Handling Exceptions Lecture 75 The "FileNotFound" and "IndexError" Exceptions Types Lecture 76 Custom Exception Creation and handling Lecture 77 JSON - Reading and Writing to a JSON File Lecture 78 Hands-on - Writing and Reading - Countries to JSON file Lecture 79 Hands-on - File Organizer Lecture 80 Python Virtual Environment and PIP Lecture 81 Setting up Virtual Environment and Installing a Package Lecture 82 Hands-on Watermarker Python Tool Lecture 83 Building an Image Watermarker in Python - Part 1 Lecture 84 Generating the Watermarked Images Lecture 85 Reading CSV File - Introduction Lecture 86 Getting the CSV header Position Lecture 87 Reading Data from a CSV Column Lecture 88 Plotting a Graph with CSV Data Section 5: Deep and Machine Learning Deep Dive Lecture 89 Deep and Machine Learning Deep Dive - Overview and Breakdown Lecture 90 Deep Learning Key Aspects Lecture 91 Deep Neural Network Dissection - Full Dive with Analogies Lecture 92 The Single Neuron Computation - Deep Dive Lecture 93 Wights - Deep Dive Lecture 94 Activation Functions - Deep Dive with Analogies Lecture 95 Deep Learning Summary Lecture 96 Machine Learning Introduction - Machine Learning vs. Deep Learning Lecture 97 Learning Types - Education System Analogy Lecture 98 Comparative Capabilities Deep Learning and Machine Learning and AI - Summary Section 6: Generative AI (GenAI) - Deep Dive Lecture 99 GenAI Introduction and Architecture Overview Lecture 100 GenAI Key Technologies - Limitations and challenges Lecture 101 GenAI Key Components Overview and Summary Section 7: LLMs (Large Language Models) - Fundamentals - A Deep Dive Lecture 102 LLMs - Overview Lecture 103 The Transformer Architecture - Fundamentals Lecture 104 The Self-Attention Mechanism - Analogy Lecture 105 The Transformers Library - Deep Dive Lecture 106 HANDS-ON - Create a Simple LLM from the Transformers Library - Simple Lecture 107 HANDS-ON - Hands-on Enhanced Transformers LLM Lecture 108 Open-source vs. Closed-source Models - Overview Section 8: OpenAI Models and Setup Lecture 109 Setup OpenAI Account and API Key Lecture 110 Using APIs Effectively in AI Projects Lecture 111 HANDS-ON - Making our First Call to OpenAI Model Section 9: Prompt Engineering - Communicating with LLMs - Deep Dive Lecture 112 Prompt Engineering Introduction Lecture 113 Prompt Engineering and Types - Why it Matters Lecture 114 HANDS-ON - Simple Prompting Example Lecture 115 Advanced Prompting Techniques and Challenges Lecture 116 HANDS-ON - Few-shots Prompting Lecture 117 HANDS-ON - Zero-shot Prompting Lecture 118 HANDS-ON -Chain-of-Thoughts Prompting Lecture 119 HANDS-ON - Instructional Prompting Lecture 120 HANDS-ON - Role-Playing and Open-ended Prompting Lecture 121 Temperature and Top-p Sampling Lecture 122 HANDS-ON - Prompt Techniques Combination and Streaming Lecture 123 Prompt Engineering Summary and Takeaways Section 10: Ollama & Open-Source Models - Complete Guide Lecture 124 Ollama - Introduction Lecture 125 Download Source Code and Resources Lecture 126 Ollama Deep Dive - Ollama Overview - What is Ollama and Advantages Lecture 127 Ollama Key Features and Use Cases Lecture 128 System Requirements & Ollama Setup - Overview Lecture 129 HANDS-ON - Download and Setup Ollama and Llama3.2 Model Lecture 130 Ollama Models Page - Overview Lecture 131 Ollama Model Parameters Deep Dive Lecture 132 Understanding Parameters and Disk Size and Computational Resources Needed Lecture 133 Ollama CLI Commands -Pull and Testing a Model Lecture 134 Pull in the Llava Multimodal Model and Caption an Image Lecture 135 Summarization and Sentiment Analysis & Customizing Our Model Lecture 136 Ollama REST API - Generate and Chat Endpoints Lecture 137 Ollama REST API - Request JSON Mode Lecture 138 Ollama Models Support Different Tasks - Summary Lecture 139 Different Ways to Interact with Ollama Models Lecture 140 Ollama Model Running Under Msty App Lecture 141 Ollama Python SDK for Building LLM Local Applications Lecture 142 HANDS-ON - Interact with Llama3 in Python Using Ollama REST API Lecture 143 Ollama Python Library - Chatting with a Model Lecture 144 Chat Example with Streaming Lecture 145 Using Ollama Show Function Lecture 146 Create a Custom Model in Code Section 11: Context & Memory Management for LLMs - Deep Dive Lecture 147 HANDS-ON - Context and Memory Management Overview Lecture 148 What is Context and Memory Management - Deep Dive Lecture 149 HANDS-ON - Adding Memory and Context to Chatbox Lecture 150 Summary Section 12: Logging in LLM Applications - Deep Dive Lecture 151 Logging - Introduction - What and the Why Lecture 152 Logging in LLM Applications and Logging Life Cycle Lecture 153 HANDS-ON - Chatbot with Logging Lecture 154 Summary Section 13: RAG - Retrieval-Augmented Generation - Deep Dive Lecture 155 RAG Introduction - What is it? Lecture 156 RAG Key Components - The RAG Triad Lecture 157 RAG vs. Pure GenAI Models Lecture 158 RAG Deep Dive - Full Diagram Walkthrough Lecture 159 RAG Benefits and Practical Applications Lecture 160 RAG Challenges Lecture 161 RAG Fundamentals - Takeaways - Summary Section 14: Vector Databases and Embeddings - Deep Dive Lecture 162 Vector Databases and Embeddings for RAG Workflows - Introduction Lecture 163 Download Source code Lecture 164 Introduction to Vector Databases - Full Overview Lecture 165 Why Vector Databases Lecture 166 Vector Databases - Benefits and Advantages Lecture 167 Traditional vs. Vector Databases - Limitations and challenges Lecture 168 Vector Databases & Embeddings - Full Overview Lecture 169 Embeddings vs. Vectors - Differences Lecture 170 Vector Databases - How They Work and Advantages Lecture 171 Vector Databases Use Cases Lecture 172 Vector and Traditional Databases - Summary Lecture 173 The Top 5 Vector Databases - Overview Lecture 174 Building Vector Databases - Dev Environment Setup Lecture 175 Setup VS-Code, Python and OpenAI API Key Lecture 176 Chroma Database workflow Lecture 177 Creating a ChromaDB and Adding Documents and Querying Lecture 178 Looping Through the Results & Showing Similarity Search Results Lecture 179 Chroma Default Embedding Function Lecture 180 Chroma Vector Database - Persisting Data and Saving Lecture 181 Creating an OpenAI Embeddings - Raw without Chroma Lecture 182 Using OpenAIs Embedding API to Create Embedding in ChromaDB Lecture 183 Vector Databases Metrics and Data Structures Lecture 184 Summary Lecture 185 Vector Similarity Deep Dive - Cosine Similarity Lecture 186 Eucledian Distance - L2 Norm Lecture 187 Dot Product Lecture 188 Summary Lecture 189 Vector Databases and LLM - Deep Dive Lecture 190 Loading all Documents Lecture 191 Generating Embeddings from Documents and Insert to Vector Database Lecture 192 Getting the Relevant Chunks when Given a Query Lecture 193 Using OpenAI LLM to Generate Response - Full Workflow Lecture 194 Summary Section 15: HANDS-ON - RAG PDF Workflow - Build RAG Workflows Deep Dive Lecture 195 Building a RAG Pipeline - Overview Lecture 196 First RAG Workflow Architectural Diagram Lecture 197 Setting up the Embedding Model Class Lecture 198 HANDS-ON - Building and Showcasing the RAG Workflow Lecture 199 HANDS-ON - RAG Workflow with UI - Streamlit Lecture 200 First RAG Pipeline Summary Section 16: HANDS-ON - Build a PDF RAG System with Text Chunking Lecture 201 PDF RAG Workflow - Architecture Overview Lecture 202 PDF and Chunk Processing and Chunk Overlap - Deep Dive Lecture 203 Setting up the SimpleRAGSystem Class and Methods Lecture 204 Testing the PDF RAG System Lecture 205 Simple PDF RAG Workflow - Summary Section 17: LLM Tools and Frameworks - LangChain Deep Dive Lecture 206 LLM Frameworks Introduction - LangChain Fundamentals Lecture 207 What is LangChain and and Main Components Lecture 208 LangChain Setup and ChatModel Lecture 209 Hands-on - LangChain ChatPromptTemplates Lecture 210 Indexes, Retrievers and Data Preparation - Overview Lecture 211 Hands-On - LangChain TextLoaders Lecture 212 Hands-on: Text Splitting and Cleaning Lecture 213 Hands-on: Embeddings and Retriever with FAISS VectorStore Lecture 214 LangChain TextSplitter - Deep Dive Lecture 215 LangChain DirectoryLoader Lecture 216 LangChain PDFLoader Lecture 217 Hands-on: LangChain Chains Lecture 218 Hands-on - Simple RAG System with Chat and LangChain Chains Lecture 219 Hands-on: Full RAG System QA Bot Using LangChain Section 18: HANDS-ON - Building LLM Applications with LangChain Lecture 220 LLM Application - News Summarizer - Architectural Overview Lecture 221 News Summarizer - Full Implementation Lecture 222 LLM Application - Youtube Video Summarizer - Architectural Overview Lecture 223 Youtube Video Summarizer & Q&A Dependency Setup Lecture 224 Youtube Video Summarizer Class Setup and Walkthrough Lecture 225 Youtube Video Summarizer Q&A - Testing the Workflow Lecture 226 LLM Application - Voice Assistant RAG System - Architectural Overview Lecture 227 Voice Assistant RAG System - Demo Lecture 228 Voice Assistant RAG System - Walkthrough and Demo Section 19: Advanced RAG Techniques - Naive vs Advanced RAG Techniques Lecture 229 RAG and the RAG Triad - Quick Overview and Recap Lecture 230 What is RAG and Naive RAG Overview and Pitfalls - Motivation Lecture 231 Deep Dive into Each Naive RAG Drawbacks Lecture 232 Advanced RAG Technique - Query Expansion with Multiple Queries - Overview Lecture 233 Hands-on - Query Expansion with Multiple Queries - Generate Multiple Queries Lecture 234 Query Expansion Workflow Architectural Diagram Lecture 235 Hands-on- Setting up the Workflow and Code Walkthrough Lecture 236 Query Expansion Full RAG Workflow Lecture 237 Query Expansion with Multiple Queries Downsides & Summary Lecture 238 Re-Ranking & Cross-encoder and Bi-encoders - Overview Lecture 239 Reranking Technique RAG System Workflow Architecture Lecture 240 Cohere Rerank API Key Setup Lecture 241 Hands-on - Re-ranking Implementation with Cohere - Full Implementation Lecture 242 Re-ranking Summary Section 20: Multimodal RAG - Deep Dive Lecture 243 Multimodal RAG Source Code Lecture 244 RAG & Multimodal RAG - Recap and Overview Lecture 245 RAG Benefits and Practical Applications Lecture 246 Multimodal RAG - Overview & Motivation and Benefits - How it Works Lecture 247 How Search Is Integrated into a Multimodal RAG System - Full Workflow Lecture 248 Why Multimodal Search is so Powerful Lecture 249 Visual Explanation Why Multimodal Search is so Powerful Lecture 250 HANDS-on: Multimodal Search System setup - Create Embeddings from Images Lecture 251 Finish the Multimodal Search System Lecture 252 HANDS-ON - Multimodal Recommender System - Overview Lecture 253 Getting our Dataset from HuggingFace & showing Number of Rows Lecture 254 Saving Images Embeddings to Vector Database Lecture 255 Testing our MultiModal Recommender System - Fetching the Correct Images Lecture 256 Setting up the RAG Workflow Lecture 257 Putting it all Together and Testing the Multimodal Recommender RAG System Lecture 258 Adding a Streamlit UI to the Multimodal Recommender System Section 21: AI Agents & Agentic Workflows - Deep Dive Lecture 259 AI Agents Deep Dive - A Full Overview Lecture 260 Agents Characteristics and Use Cases Lecture 261 Download Source Code for AI Agents Section Lecture 262 Building our First AI Agent - Project Setup (OpenAI API) Lecture 263 Build our First AI Agent - Creating the Agent Class and Prompt Lecture 264 First AI Agent - Running our First Agent and Seeing the Results Lecture 265 Passing Complex Queries Through the Agent Lecture 266 First Agent - Using a Loop to Automate our Agent Lecture 267 Adding Interactive to Our Agent - Console App Lecture 268 Agent Introduction - Section Summary Lecture 269 LangGraph - Overview & Key Concepts Lecture 270 LangGraph - How It Helps Build AI Agents Lecture 271 LangGraph Core Concepts - Simple Flow Diagrapm Lecture 272 LangGraph - Data and State - Overview Lecture 273 Building a Simple Agent with LangChain Lecture 274 LangGraph Simple Bot - Streaming Values - Console App Lecture 275 Adding Tools to our Basic LangGraph Agent Lecture 276 Adding tools to the Agent - Part 1 Lecture 277 Adding Tools to the Agent - Using Built-in Tools - Part 2 Lecture 278 Adding Memory to Our Agent State Lecture 279 Adding Human-in-the-loop to the AI Agent Lecture 280 Building AI Agents with LangChain - Section Summary Lecture 281 Hands-on - Build a Financial Report Writer AI Agent Lecture 282 Agent State and Prompts Setup Lecture 283 Creating All Nodes - Functions Lecture 284 Adding Nodes and Edges and Running our Agent Lecture 285 Adding a GUI to the Agent with Streamlit Lecture 286 Optimization Techniques - Overview Lecture 287 Financial Report Writer AI Agent - Course Summary Section 22: Fine-tuning LLMs Lecture 288 Fine-tuning Introduction - Overview Lecture 289 Fine-tuning Techniques - Overview Lecture 290 Fine-tuning Comparison of Techniques Lecture 291 Fine-tuning General Process - Overview Lecture 292 Fine-tuning OpenAI Models Pricing Lecture 293 Tokens and the Tokenizer OpenAI Tool Lecture 294 HANDS-ON - Fine-tuning an OpenAI Model - Full Walkthrough Lecture 295 Crating a Chatbot with our Fine-tuned Model and Testing Section 23: Fine-Tuning Technique - LoRA Deep Dive Lecture 296 LoRA Introduction - Benefits Lecture 297 LoRA Deep Analysis Lecture 298 LoRA Implementation Strategy Workflow Lecture 299 Hands-on - Training Models - LoRA and PEFT Lecture 300 Running LoRA Model Fine-tuning and Testing Lecture 301 Creating an API Service to Interface with Our Fine-tuned Models Lecture 302 Testing our LoRA Model API Endpoint Lecture 303 Chatting with LoRA Fine-tuned Models Lecture 304 Full LoRA Workflow - Train and Chat with Fine-tuned Models Section 24: Wrap up and Next Steps Lecture 305 Wrap up and Next Steps Developers looking to implement AI-powered document search and retrieval.,Tech Entrepreneurs & Product Managers who want to build AI-driven applications.,Students & Researchers exploring the practical applications of LLMs and AI-driven automation. Homepage: https://www.udemy.com/course/llm-engineering/ Rapidgator https://rg.to/file/9d87060c1809f5e965d0daefca9f25e3/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part01.rar.html https://rg.to/file/ffe35702cab7370225a58f3c9998eeba/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part02.rar.html https://rg.to/file/bc3596985d84f8e275e119fa0cc26d4d/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part03.rar.html https://rg.to/file/35ef52027b3701cd6d711977b70e9926/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part04.rar.html https://rg.to/file/e425388eb4671e6ff131ac6a7ede9b6d/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part05.rar.html https://rg.to/file/fd28a4304afe187d8f2aaa2ca2e6e68c/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part06.rar.html https://rg.to/file/f4e88ca151d2e3adeb5910fc810c7382/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part07.rar.html https://rg.to/file/d8f0de6b8d5bf482555d17270208d36a/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part08.rar.html https://rg.to/file/12e7352d2ca686ad9dcf2707bcc688db/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part09.rar.html https://rg.to/file/c42ebdea6a821b07d5e192a952ae4a78/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part10.rar.html https://rg.to/file/1c07d86a378b777b47633f4a5894a9ed/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part11.rar.html https://rg.to/file/4f2c935e578f1702a056427ebbf8a639/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part12.rar.html https://rg.to/file/d73d3fdb41f25e8dc509fdbfb64d2811/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part13.rar.html https://rg.to/file/387ffccbee94fda548ada910934bb279/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part14.rar.html https://rg.to/file/6c84021ea9835c14f3ac068cd24aceb8/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part15.rar.html https://rg.to/file/c7fa58a15bb9ed8c9499d283d6d41fa6/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part16.rar.html https://rg.to/file/15db714e27572e598107a7c9a0c4338a/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part17.rar.html Fikper Free Download https://fikper.com/baz4pNeIwz/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part01.rar.html https://fikper.com/wdbDmKUyoC/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part02.rar.html https://fikper.com/p09ABOOUjx/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part03.rar.html https://fikper.com/K79z7UIAjB/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part04.rar.html https://fikper.com/ERPvPnlhM7/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part05.rar.html https://fikper.com/Mk38DZTQHF/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part06.rar.html https://fikper.com/AwN1bIDZVk/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part07.rar.html https://fikper.com/5eTvENCdrn/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part08.rar.html https://fikper.com/No2z59oANK/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part09.rar.html https://fikper.com/kMpsE2ZvXD/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part10.rar.html https://fikper.com/dCToiAgJ7Q/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part11.rar.html https://fikper.com/JSCmrF09Yc/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part12.rar.html https://fikper.com/T95XMBn6kE/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part13.rar.html https://fikper.com/xUw9BMa46M/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part14.rar.html https://fikper.com/uXWggW20tg/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part15.rar.html https://fikper.com/QuPt8hqz93/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part16.rar.html https://fikper.com/1vDdrFdwQW/lkvcr.Ai..Llm.Engineering.Mastery.Genai.Rag.Complete.Guide.part17.rar.html : No Password - Links are Interchangeable

pdf | 25.03 MB | English| Isbn:1835883583 | Author: Soledad Galli; | Year: 2024 Description: Category:Computer Technology, Nonfiction TurboBit RapidGator https://rapidgator.net/file/3600ab40f18e1afbc9cfb3ed2c250174/Python.Feature.Engineering.Cookbook.3rd.Edition.-.A.complete.guide.to.crafting.powerful.features.for.your.machine.learning.models.rar AlfaFile https://alfafile.net/file/ASsHh/Python.Feature.Engineering.Cookbook.3rd.Edition.-.A.complete.guide.to.crafting.powerful.features.for.your.machine.learning.models.rar https://turbobit.net/m5h3aq1317d3/Python.Feature.Engineering.Cookbook.3rd.Edition.-.A.complete.guide.to.crafting.powerful.features.for.your.machine.learning.models.rar.html

Racecar Engineering - January 2025 English | 84 pages | True PDF | 70.5 MB Racecar Engineering is the world's leading technology publication for the motorsport industry. From aerodynamics to engines and from handling theory to manufacturing practice, Racecar Engineering is read by motorsport's top professionals. Only Racecar Engineering brings this insight every month. https://fikper.com/8wWoZsjbDV/ https://ddownload.com/4e4rsfq3ppnp https://rapidgator.net/file/d2b7e85b7869d4e51ade58dd81fb93dc/ https://nitroflare.com/view/D252CF55116C2FD/

Racecar Engineering - December 2024 English | 86 pages | True PDF | 41.5 MB Racecar Engineering is the world's leading technology publication for the motorsport industry. From aerodynamics to engines and from handling theory to manufacturing practice, Racecar Engineering is read by motorsport's top professionals. Only Racecar Engineering brings this insight every month. https://ddownload.com/4myx0ej5xpba https://rapidgator.net/file/f74c2848e965b9d81d82230f4ee7e484/ https://turbobit.net/dmzelgoc31os.html https://fileaxa.com/ds60m8ncpi4t

Free Download Udemy - Chaos Engineering Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.53 GB | Duration: 2h 42m Equip yourself with the knowledge and skills to ensure your AWS systems withstand and recover from failures. What you'll learn Chaos Engineering Fundamentals Building a Basic Fault Injection Simulation (FIS) Experiment Introduction to Real-Life Application Chaos Engineering on Compute - EC2 Chaos Engineering on Database - Aurora Chaos Engineering on Serverless - Fargate Chaos Engineering on Kubernetes - EKS Chaos Engineering on Availability Zone Requirements No prior experience or knowledge required - this course is beginner-friendly and covers everything you need to know! Description In today's fast-paced digital landscape, system resilience is vital for businesses of all sizes. "Chaos Engineering" is a comprehensive and hands-on course designed to equip you with the knowledge and skills needed to ensure your systems withstand and recover from failures. From foundational concepts to advanced applications on various AWS services, including EC2, Aurora, Fargate, and EKS, as well as strategies to ensure availability across multiple Availability Zones.What You'll Learn:Chaos Engineering Fundamentals:Understand core principles and the philosophy behind Chaos Engineering.Learn why identifying and addressing system weaknesses through controlled chaos experiments is vital.Explore essential tools and methodologies for implementing Chaos Engineering.Building a Basic Fault Injection Simulation (FIS) Experiment:Gain a step-by-step understanding of constructing and executing your first Fault Injection Simulation (FIS) experiment.Understand how to design experiments targeting different failure modes in a controlled setting.Learn to interpret experiment results and refine your simulations for better accuracy.Introduction to Real-Life Application:Discover how to apply Chaos Engineering experiments to real-world applications.Learn best practices for monitoring, capturing metrics, and analyzing results to continually improve system resilience.Chaos Engineering on Compute - EC2:Conduct chaos experiments on EC2 instances to evaluate and improve system robustness.Simulate failures, such as instance termination or network latency, and observe impacts.Chaos Engineering on Database - Aurora:Learn to apply Chaos Engineering principles to Amazon Aurora databases.Simulate failures like cluster instability or node outages and develop strategies for seamless recovery.Chaos Engineering on Serverless - Fargate:Conduct chaos experiments on AWS Fargate to test the resilience of your serverless applications.Simulate events like task failures or service downtime to ensure robust serverless architectures.Chaos Engineering on Kubernetes - EKS:Implement Chaos Engineering on Amazon EKS to stress-test Kubernetes clusters.Simulate pod failures, node crashes, and other disruptions to validate recovery mechanisms.Chaos Engineering on Availability Zone:Conduct chaos experiments across different AWS Availability Zones.Test the impact of zone failures and ensure your systems are prepared for multi-availability zone disasters.This course, with its combination of theory, demonstrations, and real-world scenarios, will enable you to build resilient systems capable of withstanding and recovering from unexpected failures efficiently. Join us to master Chaos Engineering and innovate with confidence. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Important Course Resources Section 2: Chaos Engineering Fundamentals Lecture 3 Why Chaos Engineering? Lecture 4 What is Chaos Engineering ? Lecture 5 What is AWS FIS? Lecture 6 FIS Experiments in this Course Lecture 7 Accessing the Quizzes Lecture 8 Quiz - Chaos Engineering Fundamentals Section 3: Building a basic FIS experiment Lecture 9 FIS Permissions Lecture 10 Demo - Create FIS Permissions Lecture 11 Experiment 1-Chaos Engineering on ASG Lecture 12 Built ASG based Architecture Lecture 13 Demo: ASG based Architecture Lecture 14 Create FIS Experiment Lecture 15 Demo - Run FIS Experiment Lecture 16 Demo - Demo - Learning and Improvements Lecture 17 Demo - FIS experiment -CloudWatch Dashboard Lecture 18 Demo - Create FIS Experiment using CF Lecture 19 Quiz- Building_Basis_FIS_experiment Section 4: Introduction to Real life Application Lecture 20 Introduction to our real life application Lecture 21 Pre-requisite to Deploy Application & Cloud 9 Deprecation Lecture 22 Demo: Pre-requisite to Deploy Application Lecture 23 Demo - Setup Architecture and Deploy Application Lecture 24 How to Plan Your Experiment? Part 1 Lecture 25 How to Plan Your Experiment? Part 2 Lecture 26 Establishing Steady State Metrics Using Cloudwatch RUM/X Ray Lecture 27 Demo: Cloud Formation Deployment Lecture 28 Quiz : Introduction to Real Life Application Section 5: Chaos Engineering on Compute - EC2 Lecture 29 Disk Fill Scenario on EC2 Lecture 30 Demo: FIS Experiment - Disk Fill Scenario on EC2 and before metrics in X Ray Lecture 31 Demo: FIS Experiment - After Metrics in X Ray and EC2 instances Lecture 32 Quiz - Chaos Engineering on Compute Section 6: Chaos Engineering on Database - Aurora Lecture 33 Reboot Reader Node Scenario on Aurora Lecture 34 Demo: Pre-requisite for FIS experiment, Create IAM role, and Current State Lecture 35 Demo: Create and Run FIS experiment and After Metrics and DB state Lecture 36 Quiz- Chaos Engineering on Database - Aurora Section 7: Chaos Engineering on Serverless - Fargate Lecture 37 ECS Fargate Experiment Idea and Hypothesis Lecture 38 Demo: Fargate Steady State Lecture 39 Demo: Fargate IAM role creation Lecture 40 Demo: Run experiment Task I/O stress Lecture 41 Demo: Fargate After State and Learning and Improvements Lecture 42 Quiz- Chaos Engineering on Serverless - Fargate Section 8: Chaos Engineering on Kubernetes- EKS Lecture 43 EKS Explanation Lecture 44 Demo: Memory Stress on EKS - Part 1 Lecture 45 Demo: Memory Stress on EKS - Part 2 Lecture 46 Demo: Memory Stress on EKS- Part 3 Lecture 47 Demo: Memory Stress on EKS- Part 4 Lecture 48 Pod Delete on EKS Lecture 49 Demo: Steady State Pod Delete on EKS Lecture 50 Demo: Run Experiment Pod Delete on EKS Lecture 51 Demo: Recheck After Pod Delete on EKS Lecture 52 Quiz- Chaos Engineering on Kubernetes- EKS Section 9: Chaos Engineering on Availability Zone Lecture 53 What is an Availability Zone(AZ)? Lecture 54 Experiment Overview Lecture 55 Demo: General Experiment Setup- AZ Lecture 56 Demo: Prepare Experiment- AZ Lecture 57 Running the Experiment Lecture 58 Quiz- Chaos Engineering on Availability Zone Section 10: Conclusion Lecture 59 Cleanup Process Lecture 60 Conclusion Developers interested in enhancing their systems' resilience.,Site Reliability Engineers (SREs) focused on improving system reliability.,Cloud Engineers managing AWS environments.,Technical Support Engineers specializing in fault-tolerant systems.,Technical Leads overseeing cloud-native application projects. Screenshot Homepage https://www.udemy.com/course/chaos-engineering/ Rapidgator https://rg.to/file/1964a66315e47ebf3d2a58c44656c117/prnhh.Chaos.Engineering.part2.rar.html https://rg.to/file/c36de6667d67428ddc0ee60b75fba1ec/prnhh.Chaos.Engineering.part1.rar.html Fikper Free Download https://fikper.com/DENO9tHTkL/prnhh.Chaos.Engineering.part2.rar.html https://fikper.com/tKHftxpfcI/prnhh.Chaos.Engineering.part1.rar.html No Password - Links are Interchangeable

pdf | 31.24 MB | English| Isbn:9781040223499 | Author: José A. Romagnoli, Luis Briceño-Mena, Vidhyadhar Manee | Year: 2024 Description: https://fileaxa.com/dwybbqvjhvl4 https://ddownload.com/0tkb9rmqk075 https://rapidgator.net/file/bea22ca097cb195ceb397e9bbe3c4e64/ https://turbobit.net/pvfasl252ob1.html