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Free Download Udemy - Backend Engineering with Go Published 9/2024 Created by Tiago Taquelim MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 68 Lectures ( 15h 8m ) | Size: 7.41 GB Full Guide to Building Production Backend Web Applications with Go, PostgreSQL, Docker and Deploying to the Cloud What you'll learn: Learn the Fundamentals of Web Development with Go Build Production Grade Applications with Go Learn to Weight and Think about Software Design Decisions Learn to Build and Deploy Go APIs to the Cloud Learn How to Scale and manage Traffic Learn How to Connect a Postgres Database with a Go Server Requirements: Basic Go Knowledge Description: In this project-based course, we will build a complete REST API in Go from scratch and deploy it to the cloud, ready to handle real traffic and scale affordably.Our journey begins by creating a simple TCP server, which will help us explore the net/http package in Go and understand the basics of handling network communication.Next, we'll dive into the theory behind building reliable and composable Go web applications. From there, we'll develop our project step-by-step, covering carefully curated topics such as request handling, middleware creation, database integration, request and database optimisations and rate limiting to equip you with the skills needed to ship real backend services to the cloud and manage real-world traffic efficiently.This course aims to provide you with the foundational knowledge required to build and understand backend systems, implement industry best practices, and create production-ready APIs that are secure, scalable, and maintainable. It is not just a step-by-step tutorial, but a comprehensive learning experience that prepares you for real-world scenarios.Legal Notice:All product and company names, logos, and trademarks featured on this thumbnail are the property of their respective owners. Their use in this course does not imply any affiliation, sponsorship, or endorsement by these companies. Who this course is for: Beginners and Intermediate Developers Advanced Software Engineers from Another Stack Homepage https://www.udemy.com/course/backend-engineering-with-go/ Rapidgator https://rg.to/file/65d2d9984f4edb175ebaecf7b1d242e8/hlgxg.Backend.Engineering.with.Go.part1.rar.html https://rg.to/file/eaa9283464adefa298ebaf908b0aee25/hlgxg.Backend.Engineering.with.Go.part2.rar.html https://rg.to/file/f2bdfaf9d4593e14976d2e7cebcd55bd/hlgxg.Backend.Engineering.with.Go.part3.rar.html https://rg.to/file/096e21ca2f78fd93ca0ba83fcae8ae4f/hlgxg.Backend.Engineering.with.Go.part4.rar.html https://rg.to/file/fd2777e064977260b305bf3aea7bf23c/hlgxg.Backend.Engineering.with.Go.part5.rar.html https://rg.to/file/289e8cea88659d74b2308697aca8fc4d/hlgxg.Backend.Engineering.with.Go.part6.rar.html https://rg.to/file/38799e43423541f62026a97d4c1d98ce/hlgxg.Backend.Engineering.with.Go.part7.rar.html https://rg.to/file/2050a60ec3d758a824eaad2874a4c3aa/hlgxg.Backend.Engineering.with.Go.part8.rar.html Fikper Free Download https://fikper.com/H64g81ZaNx/hlgxg.Backend.Engineering.with.Go.part1.rar.html https://fikper.com/8Myi1AnKIZ/hlgxg.Backend.Engineering.with.Go.part2.rar.html https://fikper.com/zQPQe0qJXy/hlgxg.Backend.Engineering.with.Go.part3.rar.html https://fikper.com/jcpI5YUE5l/hlgxg.Backend.Engineering.with.Go.part4.rar.html https://fikper.com/A1vu5C72cK/hlgxg.Backend.Engineering.with.Go.part5.rar.html https://fikper.com/m1tlEJVkkC/hlgxg.Backend.Engineering.with.Go.part6.rar.html https://fikper.com/Kx4JdNWBr5/hlgxg.Backend.Engineering.with.Go.part7.rar.html https://fikper.com/021Bb747bw/hlgxg.Backend.Engineering.with.Go.part8.rar.html No Password - Links are Interchangeable

Free Download O'Reilly - Chaos Engineering, Video Edition Released 3/2021 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 11h 39m | Size: 1.6 GB Auto engineers test the safety of a car by intentionally crashing it and carefully observing the results. Chaos engineering applies the same principles to software systems Auto engineers test the safety of a car by intentionally crashing it and carefully observing the results. Chaos engineering applies the same principles to software systems. In Chaos Engineering: Site reliability through controlled disruption, you'll learn to run your applications and infrastructure through a series of tests that simulate real-life failures. You'll maximize the benefits of chaos engineering by learning to think like a chaos engineer, and how to design the proper experiments to ensure the reliability of your software. With examples that cover a whole spectrum of software, you'll be ready to run an intensive testing regime on anything from a simple WordPress site to a massive distributed system running on Kubernetes. About the Technology Can your network survive a devastating failure? Could an accident bring your day-to-day operations to a halt? Chaos engineering simulates infrastructure outages, component crashes, and other calamities to show how systems and staff respond. Testing systems in distress is the best way to ensure their future resilience, which is especially important for complex, large-scale applications with little room for downtime. About the Book Chaos Engineering teaches you to design and execute controlled experiments that uncover hidden problems. Learn to inject system-shaking failures that disrupt system calls, networking, APIs, and Kubernetes-based microservices infrastructures. To help you practice, the book includes a downloadable Linux VM image with a suite of preconfigured tools so you can experiment quickly-without risk. What's Inside Inject failure into processes, applications, and virtual machines Test software running on Kubernetes Work with both open source and legacy software Simulate database connection latency Test and improve your team's failure response About the Reader Assumes Linux servers. Basic scripting skills required. About the Author Mikolaj Pawlikowski is a recognized authority on chaos engineering. He is the creator of the Kubernetes chaos engineering tool PowerfulSeal, and the networking visibility tool Goldpinger. https://www.oreilly.com/library/view/chaos-engineering/9781492043850/ TakeFile https://takefile.link/cmw4lrg1pwo2/usnmw.Chaos.Engineering.Video.Edition.part1.rar.html https://takefile.link/xhd66d1p7xig/usnmw.Chaos.Engineering.Video.Edition.part2.rar.html Rapidgator https://rg.to/file/ffe3edc20136c011fe9b2e84dd334971/usnmw.Chaos.Engineering.Video.Edition.part1.rar.html https://rg.to/file/bf752c389e2225dd15fdd4aa5ada88ae/usnmw.Chaos.Engineering.Video.Edition.part2.rar.html Fikper Free Download https://fikper.com/HPhAmYm5o3/usnmw.Chaos.Engineering.Video.Edition.part1.rar.html https://fikper.com/akUtmtRYnc/usnmw.Chaos.Engineering.Video.Edition.part2.rar.html No Password - Links are Interchangeable

Free Download Matlab Course for Wireless Communication Engineering Khaled Ramadan | Duration: 3:30 h | Video: HVC1 1280x720 | Audio: AAC 48 kHz 2ch | 1,64 GB | Language: English This is course is designed for under and post graduate students associated to the electronics and communication engineering department. It has 10 introductions of 30 minutes, each introduction discusses the theoretical explanation and the simulated figures that obtained through the explanation of the course. This course saves many months of hard work. Using the Matlab program, you will learn 1-How to estimate the Bit-Error-Rate (BER) performance of different modulation schemes like BPSK, QPSK, 16QAM, 64QAM, and 256QAM over an Additive White Gaussian Noise (AWGN) channel? 2-How to generate and add a Rayleigh fading channel based on the Jakes model? 3-How to mitigate the Rayleigh fading channel effect using different linear equalizer schemes? 4-How to estimate the Bit-Error-Rate (BER) performance over Single-Input-Single-Output Orthogonal Frequency Division Multiplexing (SISO-OFDM) communication system over a Rayleigh fading channel? 5-How to extend this work for different Multiple-Input-Multiple-Output (MIMO) configurations like 2x2, and 3x3 MIMO-OFDM communication systems over a Rayleigh fading channel? 6-A general code for BER estimation in case of NtxNr configuration for OFDM communication system over a Rayleigh fading channel will be presented, where Nt, is the number of transmitting antennas, and Nr is the number of receiving antennas. 7-Finally, the BER estimation for Non-Orthogonal Multiple Access (NOMA), which used in the 5G communication systems will be presented. Homepage https://www.udemy.com/course/matlab-course-for-wireless-communication-engineering/ Rapidgator https://rg.to/file/f89a07600ea9444fa726fcddf509359b/smned.Matlab.Course.for.Wireless.Communication.Engineering.rar.html Fikper Free Download https://fikper.com/jgZZbQvITa/smned.Matlab.Course.for.Wireless.Communication.Engineering.rar.html No Password - Links are Interchangeable

Free Download End-to-End Real-World Data Engineering Project with Snowflake Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 36m | Size: 209 MB This comprehensive course offers a hands-on deep dive into building a robust data pipeline using Snowflake, focusing on a real-world project case study. Join instructor Deepak Goyal as he shows you how to transform a data lake into a sophisticated Snowflake-based solution. Deepak covers the entire data lifecycle from ingestion to analytics-ready datasets. Learn how an end-to-end project works in Snowflake and how to implement the three-layer medallion architecture-bronze, silver, and gold. Ideal for professional data engineers as well as data analysts, this course can help you take your technical skills to the next level and put you in a more in-demand position to land the data role of your dreams. Homepage https://www.linkedin.com/learning/end-to-end-real-world-data-engineering-project-with-snowflake TakeFile https://takefile.link/huhw2edupsa1/zlmci.EndtoEnd.RealWorld.Data.Engineering.Project.with.Snowflake.rar.html Rapidgator https://rg.to/file/48d178dd0b7995edf78849d25ddfe30d/zlmci.EndtoEnd.RealWorld.Data.Engineering.Project.with.Snowflake.rar.html Fikper Free Download https://fikper.com/1MkRPyj5eD/zlmci.EndtoEnd.RealWorld.Data.Engineering.Project.with.Snowflake.rar.html No Password - Links are Interchangeable

Free Download Coursera - DeepLearning.AI Data Engineering Professional Certificate Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: Lessons () | Size: 8.88 GB Learn the principles of effective data engineering. Build your skills in the high-demand field of data engineering and learn how you can deliver real business value by applying a core set of principles and strategies for developing data systems. What you'll learn Develop a mental model for the field of data engineering as a whole, including the data engineering lifecycle and its undercurrents. Learn a framework for approaching any data engineering project you work on so you can effectively create business value with data. Build your skill in the five stages of the data engineering lifecycle; including generating, ingesting, storing, transforming, and serving data. Learn the principles of good data architecture and apply them to build data systems on the AWS cloud. Skills you'll gain Data Management DataOps Data Warehousing Data Modeling Data Management Platforms Data Architecture Data Transformation Data Engineering Data transformation Data Orchestration The DeepLearning.AI Data Engineering Professional Certificate is a comprehensive online program for data engineers and practitioners looking to start or grow their careers. Organizations of all sizes and across all industries are capturing and generating data at an ever-increasing pace. Within these organizations, every team, from executives, sales and marketing, finance and operations, product and engineering, to customer service, can derive insights and value from organizational data. Whether the end use case is data science, machine learning, or analytics, data engineering is what allows raw data to be converted to value for the business. This is why the role of data engineer is one of the highest-demand jobs in tech today. Throughout this program, you'll learn the foundations of data engineering while gaining hands-on experience designing and implementing data architectures using AWS and open-source tools. Taught by industry expert Joe Reis, co-author of Fundamentals of Data Engineering, this certificate equips you with the skills and knowledge to excel in a high-demand field, focusing on ingesting, processing, transforming, storing, and serving data to data stakeholders to drive organizational and business objectives. The practical labs were developed in partnership with AWS and Factored.AI to provide you with an authentic experience building data systems on the cloud. With this certificate, you will have the tools to further your data engineering career. Applied Learning Project In this program, you'll Translate stakeholder needs into system requirements and choose the appropriate tools to build the system. Build end-to-end batch and streaming pipelines on AWS for a product recommendation system. Apply principles of good data architecture to assess the security, performance, reliability, and scalability of data systems on AWS. Explore various types of source systems and troubleshoot common connectivity issues. Use infrastructure and pipelines as code tools to orchestrate, automate, and monitor your data pipelines. Design data lake and data lakehouse storage architectures for various use cases. Explore the impact of data storage choices on query performance and cost. Model and transform data for analytics and machine learning use cases and compare centralized processing frameworks such as Pandas with distributed processing frameworks like Spark. Serve your data to downstream data stakeholders for business analytics and machine learning use cases. 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Free Download Automotive Engineering Essentials - Drive Your Future Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.30 GB | Duration: 0h 30m Learn the Fundamentals of How Cars Work, from Engines to Electronics, and Discover the Future of Automotive Technology. What you'll learn Understand the core components of vehicle systems, including engines, transmissions, and drivetrains Analyze vehicle dynamics and how forces impact performance and handling Identify and troubleshoot common automotive problems with practical diagnostic skills Explore cutting-edge innovations in electric vehicles (EVs) and hybrid technologies Requirements No prior experience in automotive engineering is necessary-beginners are welcome! A passion for vehicles and a desire to understand how cars work Basic understanding of mechanical concepts is helpful but not required Description Unlock the Secrets Behind Every Car - Start Your Journey in Automotive Engineering Today!Are you fascinated by cars and curious about what makes them tick? Whether you're an aspiring engineer, a car enthusiast, or someone looking to expand their technical knowledge, *Automotive Engineering Essentials: Drive Your Future* is the perfect starting point for you.This comprehensive introductory course breaks down the complexities of automotive engineering into easy-to-understand lessons. From understanding the basic components of a vehicle to exploring cutting-edge technologies shaping the future of transportation, you'll gain valuable insights and practical knowledge that will fuel your passion and career aspirations.What You'll Learn:- Understanding the Automobile: Grasp the fundamental components and the evolution of cars.- Engine Mechanics: Discover how engines convert fuel into motion and the differences between gasoline and diesel engines.- Movement and Control: Learn about steering systems, braking mechanisms, and suspension for safe and smooth driving.- Car Electronics: Explore the role of batteries, electrical systems, and modern automotive technologies.- Future of Automotive Engineering: Get a glimpse into electric vehicles, self-driving cars, and emerging trends in the industry.Course Benefits:- Comprehensive Introduction: Perfect for beginners with no prior experience in automotive engineering.- Expert Instruction: Learn from experienced automotive engineers who simplify complex concepts.- Flexible Learning: Access course materials online at your own pace, anytime and anywhere.- Practical Knowledge: Apply what you learn through hands-on projects and real-world examples.- Career Advancement: Equip yourself with the knowledge needed to pursue further studies or a career in the automotive industry.Curriculum Overview:1. Understanding the Automobile - Basics of what a car is - Main components: engine, wheels, body, and controls - Evolution and history of automobiles2. How Engines Work - Engine operation and combustion process - Gasoline vs. diesel engines - Fuel conversion into mechanical energy3. Movement and Control - Steering systems and how they work - Braking mechanisms and safety features - Suspension systems for stability and comfort4. Introduction to Car Electronics - Role of the car battery and electrical systems - Basic electrical components: lights, dashboard, starter - Modern automotive technologies and sensors5. The Future of Automotive Engineering - Electric vehicles and their technology - Self-driving cars and autonomous systems - Emerging trends and innovations in the automotive industryWho This Course is For:- *Aspiring Automotive Engineers:* Lay a strong foundation for a successful career in automotive engineering.- *Car Enthusiasts:* Deepen your understanding of how your favorite vehicles work.- *DIY Mechanics:* Enhance your ability to maintain and repair cars with technical knowledge.- *Students and Educators:* Supplement your studies or teaching materials with comprehensive automotive insights.- *Professionals Seeking a Career Change:* Transition into the automotive industry with essential engineering knowledge.Testimonials: "This course made automotive engineering accessible and engaging. I never thought I could understand how engines work, but the lessons were clear and easy to follow!" - Alex M., Course Graduate "As a car enthusiast, I found this course incredibly insightful. It deepened my appreciation for the engineering that goes into every vehicle." - Jamie L., Automotive Hobbyist "The hands-on projects and real-world examples helped me grasp complex concepts quickly. Highly recommend for anyone interested in automotive technology." - Taylor S., Aspiring EngineerCall to Action:Ready to Ignite Your Passion for Automotive Engineering?Enroll in Automotive Engineering Essentials: Drive Your Future today and take the first step towards mastering the technology that powers the vehicles of tomorrow. Don't miss out on this opportunity to accelerate your knowledge and drive your career forward!Enroll Now---Frequently Asked Questions:Q: Do I need any prior knowledge in engineering to take this course?A: No prior experience is required. This course is designed for beginners and anyone interested in learning about automotive engineering.Q: How long do I have access to the course materials?A: Once enrolled, you will have lifetime access to all course materials, including any updates or additions.Q: Will there be any hands-on projects? A: Yes, the course includes practical projects and real-world examples to help you apply what you've learned.Q: Is there a certificate upon completion?A: Yes, you will receive a certificate of completion that you can showcase on your resume or LinkedIn profile. Overview Section 1: Introduction Lecture 1 Automotive Engineering 101 Lecture 2 Understanding Car Engines 1 Lecture 3 Understanding Car Engines 2 Lecture 4 Unlocking Car Electronics Lecture 5 The Future of Cars Lecture 6 Congrats on Completing the Automotive Engineering Aspiring automotive engineers looking to build a solid foundation in the field,Automotive enthusiasts who want to deepen their technical understanding of vehicle mechanics,Mechanical engineering students interested in specializing in automotive engineering,Technicians and mechanics aiming to upgrade their skills with advanced engineering knowledge Homepage https://www.udemy.com/course/automotive-engineering-essentials-drive-your-future/ Rapidgator https://rg.to/file/3a52df04e586e4230beee693955d6837/pezgw.Automotive.Engineering.Essentials.Drive.Your.Future.part1.rar.html https://rg.to/file/45c9eb44cecb738847845f7a50d410de/pezgw.Automotive.Engineering.Essentials.Drive.Your.Future.part2.rar.html Fikper Free Download https://fikper.com/N8fcwEMbIz/pezgw.Automotive.Engineering.Essentials.Drive.Your.Future.part1.rar.html https://fikper.com/kwP9qs0HiH/pezgw.Automotive.Engineering.Essentials.Drive.Your.Future.part2.rar.html No Password - Links are Interchangeable

Free Download Platform Engineering - Build Scalable & Resilient Systems Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 21.50 GB | Duration: 40h 5m Learn DevOps, Infrastructure as Code, CI/CD, Kubernetes, more. Prepare for a successful career in platform engineering! What you'll learn Understand and Define Platform Engineering: Grasp the fundamental concepts, importance, benefits, and challenges of Platform Engineering. Master Infrastructure as Code (IaC): Implement IaC effectively using tools like Terraform and Ansible, enabling consistent & automated infrastructure. Design and Implement CI/CD Pipelines: Understand the principles of Continuous Integration & Continuous Delivery, build efficient pipelines, apply best practices Embrace Cloud-Native Technologies: Learn benefits & challenges of cloud-native architectures, hands-on with Kubernetes for container orchestration & deployment. Leverage Observability Tools: Implement monitoring, logging, and metrics collection with tools like Prometheus and Grafana for platform performance and health. Understand Platform Design Principles: Apply key design principles to build self-service platforms that empower development teams and improve overall efficiency Prepare for Platform Engineering Interviews: Develop a strong resume, practice answering common interview questions, and gain confidence through mock interviews Apply Platform Engineering Principles in Real-World Scenarios: Understand practical examples & implementation strategies to bridge gap between theory & practice Enhance Collaboration and Communication Skills: Foster DevOps culture necessary for effective collaboration and communication within cross-functional teams. Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Platform Engineering: Build Scalable & Resilient Systems course by Uplatz.Platform Engineering is a discipline in software development focused on building and maintaining an internal platform that enhances the productivity and efficiency of developers and operations teams. The goal is to provide reusable, scalable, and automated infrastructure solutions that streamline the software development lifecycle, enabling faster delivery of applications.In essence, platform engineering allows for the creation of a standardized, highly automated environment where developers can focus on writing code, while platform engineers manage the complexity of the underlying infrastructure. This leads to improved developer experience, faster deployments, and reduced operational overhead.Key Aspects of Platform Engineering:Internal Developer Platform (IDP): Platform engineers design and build IDPs, which are custom platforms tailored to meet the specific needs of the development teams within an organization. These platforms typically abstract away complex infrastructure concerns, providing a unified and self-service environment where developers can easily deploy, monitor, and manage their applications.Automation: A core principle of platform engineering is automation. This includes automating infrastructure provisioning (using Infrastructure as Code), CI/CD pipelines, monitoring, and logging. The aim is to reduce manual intervention and repetitive tasks.Self-Service Capabilities: The platform provides self-service tools, allowing developers to independently create environments, deploy applications, and troubleshoot issues without relying on other teams (such as DevOps). This boosts developer autonomy and shortens development cycles.Scalability and Reliability: Platforms built by platform engineers are designed to scale with the needs of the business. They integrate fault-tolerance, monitoring, and observability to ensure high availability and reliability, crucial for large-scale applications.Collaboration between DevOps, Security, and Developers: Platform engineering bridges the gap between DevOps teams, developers, and security teams. It aligns infrastructure, tooling, and workflows with the requirements of each group, ensuring compliance, security, and faster software delivery.How Platform Engineering Works:Infrastructure as Code (IaC): Platform engineers use IaC tools (like Terraform, Ansible, or Pulumi) to automate and manage the underlying infrastructure, ensuring it can be provisioned and maintained consistently across different environments (development, staging, production).CI/CD Pipeline Integration: They integrate Continuous Integration/Continuous Deployment (CI/CD) pipelines into the platform. This involves tools like Jenkins, GitLab CI, or GitHub Actions to automate testing, building, and deployment processes.Containerization and Orchestration: Platform engineers leverage containers (e.g., Docker) and orchestration platforms (like Kubernetes) to abstract applications from the underlying infrastructure, making deployments consistent and scalable across environments.Observability and Monitoring: Platform engineers implement monitoring, logging, and alerting tools (e.g., Prometheus, Grafana, ELK Stack) to ensure the health, performance, and security of the applications running on the platform. These insights help in proactive troubleshooting and maintenance.Security and Governance: Security best practices are embedded into the platform, such as managing secrets (with HashiCorp Vault), ensuring compliance with organizational standards, and enforcing access control and security policies.Collaboration and Tooling: Tools are designed with usability in mind, allowing developers to access necessary resources through a unified interface (like a dashboard or CLI). This allows for consistent communication between platform engineers and development teams to ensure the platform evolves with their needs.Platform Engineering - Course CurriculumModule 1: Introduction to Platform EngineeringLecture 1: Define Platform Engineering, its importance, benefits, and challenges. Discuss the future of Platform Engineering.Module 2: Core ConceptsLecture 2: Explore the benefits of Infrastructure as Code (IaC) and learn about popular tools like Terraform and Ansible.Lecture 3: Understand CI/CD pipelines, their components, and best practices.Lecture 4: Learn about self-service platforms, their purpose, and design principles. Explore Platform APIs, their role, and development considerations.Lecture 5: Master platform observability, including metrics, logging, and monitoring.Lecture 6: Deep dive into platform observability, monitoring, and the future of observability.Module 3: Cloud-NativeLecture 7: Introduction to cloud-native concepts, benefits, and challenges.Lecture 8: Real-world examples of cloud-native and its future.Lecture 9: Introduction to Kubernetes architecture, components, and cluster management.Lecture 10: Container orchestration, deployment strategies, and best practices.Lecture 11: Serverless computing, use cases, benefits, challenges, and future.Lecture 12: Cloud security, best practices, and common threats.Module 4: Design Principles and Shell ScriptingLecture 13: Understand the design principles behind platform engineering.Lecture 14: Recap and connect the terminologies learned so far.Lecture 15 & 16: Introduction to Shell Scripting.Lecture 17: Implementation of Shell Commands and Cocalc.Lecture 18: CHMO - Understanding Programming BasicsModule 5: Kubernetes and Platform LifecycleLecture 19 & 20: Implementation of Kubernetes.Lecture 21: Platform lifecycle management, including planning, development, deployment, and operations.Module 6: Observability with GrafanaLecture 22: Understanding Grafana for observability.Lecture 23: Connecting Grafana and other automation tools.Lecture 24: Grafana Labs connections.Module 7: DevOps and ToolingLecture 25: Understanding Jenkins.Lecture 26: Connection between Kubernetes and JenkinsLecture 27: DevOps implementationLecture 28: Service connectionLecture 29: Platform Engineering documentationLecture 30: Understanding Redhat OpenShiftLecture 31: Understanding GitLabModule 8: Practical Examples and Interview PreparationLecture 32: Practical examples of Platform Engineering and implementationLecture 33 & 34: How to make a resume for Platform Engineering rolesLecture 35 & 36: Common Platform Engineering interview questions and answersLecture 37: Tips and rules for interviewsLecture 38, 39 & 40: Company-oriented interview questionsLecture 41: Top questions and framing answersLecture 42: LinkedIn sessionCourse RecapFinal Lecture: Review key concepts, achievements, and next steps.Benefits of Learning Platform Engineering1. Enhanced Career OpportunitiesPlatform engineering is a rapidly growing field with high demand for skilled professionals. By mastering platform engineering, you'll unlock a wealth of career opportunities, including roles such as:Platform EngineerCloud ArchitectDevOps EngineerSite Reliability Engineer (SRE)Software Engineer specializing in InfrastructureTechnical Lead or Manager2. Increased Earning PotentialDue to the high demand and specialized skillset required, platform engineers command competitive salaries and benefits.3. Improved Technical SkillsYou'll gain proficiency in a wide array of cutting-edge technologies and tools, including:Infrastructure as Code (IaC) (Terraform, Ansible)CI/CD Pipelines (Jenkins, GitLab CI/CD)Container Orchestration (Kubernetes)Cloud Platforms (AWS, Azure, GCP)Monitoring and Observability (Prometheus, Grafana)4. Greater Impact and InfluencePlatform engineers play a crucial role in enabling and empowering development teams. You'll have a direct impact on the efficiency, productivity, and success of the entire organization.5. Problem-Solving and InnovationYou'll be challenged to think critically, solve complex problems, and find creative solutions to streamline software delivery and optimize the development experience.6. Professional Growth and DevelopmentPlatform engineering is a constantly evolving field. By staying current with emerging trends and technologies, you'll ensure continuous professional growth and development.Career Path in Platform EngineeringThe typical career path in platform engineering often starts with roles like:Software Engineer/Developer: Gaining experience in building and deploying applications lays a strong foundation for understanding developer needs and pain points.DevOps Engineer: Building on development experience, DevOps engineers gain experience in automating and streamlining the software delivery process.System Administrator: Experience in managing and maintaining infrastructure can be leveraged to transition into automating infrastructure provisioning and management.From there, individuals can progress into specialized platform engineering roles, such as:Platform Engineer: Focus on designing, building, and maintaining internal developer platforms.Cloud Architect: Design and implement cloud solutions incorporating platform engineering principles.Site Reliability Engineer (SRE): Focus on ensuring the reliability and performance of the platform and its applications.With experience and expertise, platform engineers can move into leadership positions like:Technical Lead or Manager: Lead and mentor teams of platform engineers.Director of Platform Engineering: Oversee the strategy and execution of platform initiatives across the organization. Overview Section 1: Introduction to Platform Engineering - Benefits, Challenges, Future Lecture 1 Introduction to Platform Engineering - Benefits, Challenges, Future Section 2: Infrastructure-as-Code (IaC) with Terraform and Ansible Lecture 2 Infrastructure-as-Code (IaC) with Terraform and Ansible Section 3: Continuous Integration (CI) and Continuous Delivery (CD) Lecture 3 Continuous Integration (CI) and Continuous Delivery (CD) Section 4: API and Platform API Lecture 4 API and Platform API Section 5: Platform Observability - Metrics and Logging Lecture 5 Platform Observability - Metrics and Logging Section 6: Platform Observability - Monitoring and Future of Observability Lecture 6 Part 1 - Platform Observability - Monitoring and Future of Observability Lecture 7 Part 2 - Platform Observability - Monitoring and Future of Observability Section 7: Introduction to Cloud Native - Benefits and Challenges Lecture 8 Introduction to Cloud Native - Benefits and Challenges Section 8: Real-world Example of Cloud Native and Future Aspects Lecture 9 Real-world Example of Cloud Native and Future Aspects Section 9: Introduction to Kubernetes Lecture 10 Introduction to Kubernetes Section 10: Container Orchestration Lecture 11 Container Orchestration Section 11: Serverless Computing - Benefits, Challenges, Future Lecture 12 Serverless Computing - Benefits, Challenges, Future Section 12: Cloud Security - Best Practices and Future Lecture 13 Cloud Security - Best Practices and Future Section 13: Understanding the Design Principles Lecture 14 Understanding the Design Principles Section 14: Recap and Connecting the Terminologies Lecture 15 Recap and Connecting the Terminologies Section 15: Understand Shell Scripting Lecture 16 Part 1 - Understand Shell Scripting Lecture 17 Part 2 - Understand Shell Scripting Section 16: Shell Commands and CoCalc (Collaborative Calculation and Data Science) Lecture 18 Shell Commands and CoCalc (Collaborative Calculation and Data Science) Section 17: Understand Programming Basics Lecture 19 Understand Programming Basics Section 18: Implementation of Kubernetes Lecture 20 Part 1 - Implementation of Kubernetes Lecture 21 Part 2 - Implementation of Kubernetes Section 19: Platform Lifecycle Lecture 22 Platform Lifecycle Section 20: Grafana Lecture 23 Grafana for Observability Lecture 24 Connecting Grafana and other Automation Tools Lecture 25 Grafana Labs Connections Section 21: Understanding Jenkins Lecture 26 Understanding Jenkins Section 22: Connection between Kubernetes and Jenkins Lecture 27 Connection between Kubernetes and Jenkins Section 23: DevOps Implementation Lecture 28 DevOps Implementation Section 24: Service Connection Lecture 29 Service Connection Section 25: Platform Engineering Documentation Lecture 30 Platform Engineering Documentation Section 26: Red Hat OpenShift Lecture 31 Red Hat OpenShift Section 27: Understanding GitLab Lecture 32 Understanding GitLab Section 28: Practical Example of Platform Engineering and its Implementation Lecture 33 Practical Example of Platform Engineering and its Implementation Section 29: How to make Resume for Platform Engineering and DevOps Lecture 34 Part 1 - How to make Resume for Platform Engineering and DevOps Lecture 35 Part 2 - How to make Resume for Platform Engineering and DevOps Section 30: Interview Questions on Platform Engineering Lecture 36 Part 1 - Interview Questions on Platform Engineering Lecture 37 Part 2 - Interview Questions on Platform Engineering Section 31: Tips and Key Points for Platform Engineer Interview Lecture 38 Tips and Key Points for Platform Engineer Interview Section 32: Company-oriented PE Interview Questions Lecture 39 Part 1 - Company-oriented PE Interview Questions Lecture 40 Part 2 - Company-oriented PE Interview Questions Lecture 41 Part 3 - Company-oriented PE Interview Questions Section 33: Top Questions and Framing Answers for Platform Engineer Interviews Lecture 42 Top Questions and Framing Answers for Platform Engineer Interviews Section 34: LinkedIn Profile for a Platform Engineer Lecture 43 LinkedIn Profile for a Platform Engineer Software Engineers and Developers: Those who want to expand their skill set beyond application development and gain expertise in building and managing the underlying platforms that support software delivery.,DevOps Engineers: Those looking to deepen their understanding of platform engineering principles and tools to streamline development, deployment, and operations processes.,Platform Engineers: Those already working in platform engineering roles seeking to expand their knowledge, learn new tools and techniques, and stay current with industry best practices.,Beginners and newbies aspiring for a career in cloud and platform engineering.,Anyone interested in learning DevOps, platform engineering, and site reliability engineering both from architecture and implementation point of view.,Cloud Architects: Those responsible for designing and implementing cloud solutions at scale, and looking to integrate platform engineering principles into their overall architecture.,Cloud Engineers: Those seeking to enhance their knowledge of cloud-native technologies and their application in building scalable and resilient platforms.,System Administrators: Those transitioning to a more development-centric role and wanting to learn how to automate and manage infrastructure using code.,IT Professionals: Those aspiring to move into the growing field of platform engineering and gain a competitive edge in the job market.,Technical Leaders and Managers: Those responsible for overseeing software development and infrastructure teams and seeking to optimize their processes and improve delivery efficiency. 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Free Download C/C++ Programming For Mechanical Engineering(Using Chatgpt) Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 5.03 GB | Duration: 8h 31m AI Powered C/C++ Programming for Core Engineering What you'll learn Understand C/C++ Basics How to Use ChatGPT for Programming Integration of C/C++ with real-world industrial systems. AI tools for code optimization and debugging. Requirements Laptop/PC with Internet Connection Description Unlock the power of C/C++ programming tailored for core engineers working in the rapidly evolving fields of Industry 4.0.This course blends traditional C/C++ coding practices with AI-driven insights, equipping you with modern problem-solving techniques.Specifically designed for professionals in manufacturing, mechanical, and industrial sectors, this program emphasizes hands-on coding experience, automation, and smart learning strategies through tools like ChatGPT.Throughout this course, you'll learn how to:Master foundational and advanced C/C++ programming concepts.Implement AI-based solutions to streamline complex engineering processes.Integrate programming with mechanical and industrial systems for Industry 4.0 applications.Develop code for real-time industrial automation and intelligent systems.RequirementsAccess to a computer.Willingness to explore AI tools like ChatGPT for smart coding.AudienceMechanical, manufacturing, and industrial engineers.Professionals in Industry 4.0 looking to enhance coding skills.Engineers seeking AI-driven solutions for automation and real-time applications.Those interested in integrating C/C++ with industrial systems.What Will You Learn?Core C/C++ programming skills.AI tools for code optimization and debugging.Integration of C/C++ with real-world industrial systems.In this course, students will:Understand C/C++ Basics: Learn fundamental programming concepts and terminology.Write Simple Programs: Develop and run basic C/C++ applications using an IDE.Control Program Flow: Utilize conditional statements and loops to manage program execution.Create Functions: Design reusable functions and explore recursion.Work with Data Structures: Manage data using arrays, strings, and pointers.Apply Object-Oriented Programming: Model mechanical systems with classes and objects.Handle File I/O: Read from and write to files for data storage and retrieval.Implement Numerical Methods: Solve engineering problems using basic algorithms.Complete a Practical Project: Develop a capstone project applying programming skills to real-world mechanical engineering challenges. Overview Section 1: Introduction to Programming Lecture 1 Overview of Programming Languages Section 2: Setting Up the Development Environment Lecture 2 Setting Up the Development Environment Section 3: Basic Syntax and Data Types Lecture 3 Variables, Data Types (int, float, char, etc.) Lecture 4 Operators (Arithmetic, Logical, Relational) Section 4: Decision Making Lecture 5 Decision Making Section 5: Loops Lecture 6 for loop, while loop, do-while loo Lecture 7 Nested Loops Section 6: Introduction to Functions Lecture 8 Defining and Calling Functions Section 7: Introduction to Arrays Lecture 9 Arrays Section 8: Pointers Lecture 10 Basics of Pointers Lecture 11 Pointers and Functions (Use of ChatGPT) Section 9: Strings Lecture 12 String Manipulation Section 10: Structures in C/C++ Lecture 13 Defining and Using Structures Section 11: File Handling Lecture 14 Reading from and Writing to Files and Binary File Operations Section 12: Practical Application in Mechanical Engineering Lecture 15 Practical Application in Mechanical Engineering Section 13: Introduction to OOP Lecture 16 OOP Section 14: Inheritance and Polymorphism Lecture 17 Inheritance and Polymorphism Section 15: Encapsulation and Abstraction Lecture 18 Access Specifiers (Private, Public, Protected) , Abstract Classes and Interfaces Section 16: Dynamic Memory Allocation Lecture 19 Dynamic Memory Allocation Section 17: Templates and STL (Standard Template Library) Lecture 20 Templates and STL Section 18: Error Handling and Debugging Lecture 21 Error Handling and Debugging Section 19: Numerical Methods in C/C++ Lecture 22 Numerical Methods in C/C++ Section 20: Simulation and Modelling Lecture 23 Simulation and Modelling Section 21: Case Study: Real-World Application Lecture 24 Building a Small Project Mechanical, manufacturing, and industrial engineers.,Mechanical Engineers students,Any Core Engineering students and Engineers Homepage https://www.udemy.com/course/c-and-c-plus-plus-programming-for-mechanical-engineering/ Rapidgator https://rg.to/file/2224c64c7bd8640565877683a90dd63c/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part1.rar.html https://rg.to/file/dd587be9c5630f695027492fa40d0b1f/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part2.rar.html https://rg.to/file/9b548c3452a117d60afc7f2719a2a902/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part3.rar.html https://rg.to/file/668cb1a59ef11914e3af961c72b800ac/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part4.rar.html https://rg.to/file/f1801e95ba67bea886f0b7f3970145f8/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part5.rar.html https://rg.to/file/7eefa79d2a3d503314935d34890c80a5/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part6.rar.html Fikper Free Download https://fikper.com/uVPN1NiTfJ/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part1.rar.html https://fikper.com/8uaOfkxD5u/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part2.rar.html https://fikper.com/KeezhgOFU2/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part3.rar.html https://fikper.com/qFMHz5xts8/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part4.rar.html https://fikper.com/wkRhAyovAz/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part5.rar.html https://fikper.com/QGgAHf89H9/xzunb.CC.Programming.For.Mechanical.EngineeringUsing.Chatgpt.part6.rar.html No Password - Links are Interchangeable

Free Download Udemy - Foundations of Reverse Engineering Last updated 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 45m | Size: 713 MB Reverse Engineering Essentials: Converting Physical Objects to CAD Models What you'll learn Fundamentals of Reverse Engineering Physical Measurement Techniques 3D Scanning Technology Post-Processing of Scan Data Troubleshooting Common Issues Model Inspection and Verification Requirements Understanding of Engineering Concepts: A fundamental grasp of engineering principles and design concepts is beneficial. Description In this course you will learn the fundamentals of reverse engineering. Are you tasked with working on designs that predate CAD technology, or need to create accessories for third-party products? This course is tailored for you. Dive into the essential principles of reverse engineering and discover how to translate physical objects into accurate digital models.In this hands-on course, you'll learn to use various tools and techniques to measure and analyze real-world objects. Explore the fundamentals of physical measurement, 3D scanning, and touch probes, and see how to integrate these measurements into your preferred CAD software.We'll guide you through the entire reverse engineering process, from capturing raw data to refining and inspecting the final CAD models. You'll also gain insights into effective post-processing of scan data to ensure precision and quality in your designs.Additionally, the course will cover best practices for integrating reverse-engineered parts into existing systems and addressing common challenges that arise during the process. Learn to optimize workflows, troubleshoot issues, and adapt techniques to various scenarios to enhance your design capabilities. By the end of this course, you'll be equipped to handle legacy designs and create custom solutions with confidence, bridging the gap between physical and digital realms. Who this course is for Product Developers, CAD Technicians, Engineers and Designers Homepage https://www.udemy.com/course/foundations-of-reverse-engineering/ Rapidgator https://rg.to/file/08cd647f9b7ec991537c34c4eabd9da0/nmgfs.Foundations.of.Reverse.Engineering.rar.html Fikper Free Download https://fikper.com/4wxYtqlZnf/nmgfs.Foundations.of.Reverse.Engineering.rar.html No Password - Links are Interchangeable

Free Download AI for Everyone - Generative AI with Prompt Engineering Published 9/2024 Created by Navveen Balani MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 44 Lectures ( 2h 24m ) | Size: 1.48 GB Practical AI: Unlock Productivity and Creativity with Generative AI Tools like ChatGPT and Gemini for Real-World Success What you'll learn: Learn the core concepts of AI and its use in industries such as healthcare, entertainment, and business. Gain insights into how generative AI works and its applications, including models like GPT and Gemini. Develop skills in crafting clear, precise prompts to guide AI models, optimizing their output for various creative and productive tasks. Discover how to leverage AI tools for streamlining operations, boosting creativity, and improving decision-making in real-world scenarios. Understand the ethical considerations surrounding AI use, including fairness, transparency, and accountability in AI-driven solutions. Explore the techniques of multi-agent prompt engineering to handle complex tasks and expand AI's focus for comprehensive solutions. Unlock the potential of AI in fostering innovation across different domains by applying advanced AI models effectively. Requirements: Basic understanding of computers and the internet No prior AI or programming knowledge is needed Willingness to learn new tools Description: "Anyone can learn and apply AI" - Yes, that's right! Regardless of your background or prior knowledge, you can harness the transformative power of artificial intelligence. This course, "Practical AI: Unlock Productivity and Creativity with Generative AI Tools like ChatGPT and Gemini," is designed to democratize AI, making it accessible, practical, and usable for everyone.In this course, you will explore the art and science of prompt engineering, learning how to communicate effectively with advanced AI models like ChatGPT and Gemini. Through practical insights and real-world applications, we bridge the gap between complex AI technologies and everyday use, empowering you to tailor AI responses to meet your specific needs and drive innovation.This course is led by an award-winning author and LinkedIn Top Voice in AI, offering expert guidance based on over two decades of experience. You'll quickly master essential AI concepts, including ethical prompt engineering and AI-driven solutions for productivity, creativity, and innovation.Key Course Takeaways:AI for Everyone: Learn AI in an easy, accessible way, designed for both beginners and advanced users.Real-World Applications: Discover how AI can enhance your work and creativity, solving real-life challenges.Ethical AI Practices: Craft responsible, impactful prompts that ensure AI benefits society.Expert Mentorship: Receive guidance from a leading AI expert, with insights from years of hands-on experience.Who Should Enroll:This course is perfect for professionals, creatives, and anyone curious about AI. Whether you aim to boost business productivity, explore new creative mediums, or simply learn how to work with AI, this course will equip you with the tools to succeed.Upon completion, you'll master prompt engineering, unlocking innovative solutions to enhance productivity and creativity. Join us in making AI a core part of your future! Who this course is for: Beginners curious about AI: No prior experience is required, making it perfect for those new to AI who want to gain foundational knowledge. Professionals seeking productivity with AI: Business professionals and entrepreneurs looking to leverage AI-powered tools like GPT and Gemini for enhancing workflows and creativity. Creative professionals: Writers, designers, and marketers interested in using Generative AI for content creation, innovation, and design. Tech enthusiasts: Individuals eager to explore Generative AI, Large Language Models (LLMs), and prompt engineering techniques to optimize AI outputs Students and educators: Learners interested in gaining hands-on experience with AI tools, understanding multi-agent prompt engineering, and its academic and real-world applications. Anyone interested in ethical AI: People looking to explore the ethical aspects of AI development and responsible usage. Homepage https://anonymz.com/https://www.udemy.com/course/ai-for-everyone-generative-ai-with-prompt-engineering/ Rapidgator https://rg.to/file/5b13756d9cdcbd5cf923771c34ebb526/jktte.AI.for.Everyone.Generative.AI.with.Prompt.Engineering.part1.rar.html https://rg.to/file/be693957b2a7c99542409037e7e8a12f/jktte.AI.for.Everyone.Generative.AI.with.Prompt.Engineering.part2.rar.html Fikper Free Download https://fikper.com/yVJWcuyPGE/jktte.AI.for.Everyone.Generative.AI.with.Prompt.Engineering.part1.rar.html https://fikper.com/urk9PeHGwv/jktte.AI.for.Everyone.Generative.AI.with.Prompt.Engineering.part2.rar.html No Password - Links are Interchangeable

Free Download Security Engineering - Secure Endpoints Published 1/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz Language: English | Size: 97.16 MB | Duration: 45m 3s Endpoint security is an important consideration when evaluating the overall security of your systems. This course will teach you how to harden and monitor Windows, Linux, and container endpoints. Are you looking to secure Windows, Linux, and container endpoints on your network? In this course, Security Engineering: Secure Endpoints, you'll learn to harden and monitor endpoints on an enterprise network. First, you'll explore endpoint monitoring. Next, you'll discover endpoint and container hardening. Finally, you'll learn how to maintain file integrity. When you're finished with this course, you'll have the skills and knowledge of Security Engineering needed to configure secure endpoints. Homepage https://www.pluralsight.com/courses/sec-engineering-secure-endpoints TakeFile https://takefile.link/cl4akcszjvqh/ptocr.Security.Engineering.Secure.Endpoints.rar.html Rapidgator https://rg.to/file/e9eaeda06aeb15ab4a77dfb4c039b18a/ptocr.Security.Engineering.Secure.Endpoints.rar.html Fikper Free Download https://fikper.com/Ta1lAXy2y8/ptocr.Security.Engineering.Secure.Endpoints.rar.html No Password - Links are Interchangeable

Free Download Security Engineering - Asset Evaluation and Execution Plan Published 4/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz Language: English | Size: 167.41 MB | Duration: 1h 10m 39s This course empowers you with the vital skills needed for asset inventory, management practices, and creating an execution plan. Globomantics, a multi-billion-dollar tech innovator, has recently acquired several smaller companies. They have tasked their security team with determining the security posture of these newly acquired assets and the most effective methods to protect them. Your team has been assigned the responsibility of conducting a comprehensive evaluation of Globomantics' assets across their expanding infrastructure. The initial step involves establishing robust asset inventory and management practices. In this course, Security Engineering: Asset Evaluation and Execution Plan, you will learn techniques to catalog all critical systems, applications, and data repositories, ensuring a thorough understanding of their asset landscape. Following this, you will conduct thorough asset assessments to uncover potential weaknesses or misconfigurations that may expose Globomantics to cyber threats. This entails analyzing software versions, service configurations, access controls, and more across the identified assets. Finally, based on your findings, you will create a detailed engineering execution plan outlining the necessary steps to address vulnerabilities and strengthen Globomantics' security posture. This plan will include implementing customized access controls, updating software, reconfiguring services, and establishing continuous monitoring processes. The security of Globomantics' acquisitions relies on your ability to meticulously evaluate their assets, identify risks, and devise a robust security strategy. When you are finished with this course, you will have the expertise in asset management, assessment, and execution planning to safeguard their newly acquired entities and establishing a resilient security architecture for their expanding enterprise. Homepage https://www.pluralsight.com/courses/sec-engineering-asset-evaluation-execution-plan TakeFile https://takefile.link/xtsu02mn7bn6/syyww.Security.Engineering.Asset.Evaluation.and.Execution.Plan.rar.html Rapidgator https://rg.to/file/d1afd65283f7c65b7f07f6fb973910b8/syyww.Security.Engineering.Asset.Evaluation.and.Execution.Plan.rar.html Fikper Free Download https://fikper.com/M0OaO4B2cN/syyww.Security.Engineering.Asset.Evaluation.and.Execution.Plan.rar.html No Password - Links are Interchangeable

Free Download Mastering Gen Ai - Prompt Engineering - A Hands-On Guide Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.37 GB | Duration: 3h 7m Hands-on Training in Generative AI - Prompt Engineering What you'll learn Grasp Generative AI Fundamentals: Learn core concepts, applications, and models. Master Prompt Engineering: Design, optimize, and troubleshoot effective prompts. Build and Customize Prompts: Develop and fine-tune prompt frameworks for various tasks. Apply Advanced Techniques: Explore advanced concepts and real-world applications of Generative AI. Requirements Basic Computer Skills: Familiarity with using a computer and navigating software applications. Introduction to AI Concepts: A basic understanding of artificial intelligence is helpful but not required. No Prior Experience Needed: The course is designed for beginners, so no prior experience in Generative AI or prompt engineering is necessary. Access to a Computer: A computer with an internet connection for accessing course materials and completing hands-on exercises. Description Dive into the world of Generative AI with our comprehensive course designed for learners at all levels. "Generative AI and Prompt Engineering: A Hands-on Guide" offers a thorough exploration of Generative AI technologies and practical techniques for effective prompt engineering.In this course, you will:Understand Generative AI: Gain a solid foundation in what Generative AI is, its various models, and its real-world applications.Master Prompt Engineering: Learn how to craft and optimize prompts to guide AI models, including best practices and strategies for overcoming common challenges.Build Practical Skills: Develop hands-on experience by creating and customizing prompt frameworks, with step-by-step guidance on setting up your development environment and fine-tuning models.Explore Advanced Topics: Delve into advanced concepts such as transfer learning and zero-shot learning, and see how these techniques apply to real-world scenarios through detailed case studies.Whether you're new to AI or looking to enhance your existing knowledge, this course provides the tools and insights needed to effectively leverage Generative AI and prompt engineering in your projects. With engaging content, practical exercises, and real-world examples, you will build a strong foundation and gain confidence in applying these cutting-edge technologies. Join us to unlock the potential of AI and advance your skills with practical, real-world applications and interactive learning experiences. Overview Section 1: Introduction to Generative AI Lecture 1 Overview of Generative AI Lecture 2 Key Applications of Generative AI Lecture 3 A Brief History of Generative AI Lecture 4 Types of Generative AI Models Section 2: Fundamentals of Prompt Engineering Lecture 5 Understanding Prompts in AI Lecture 6 Demo - Understanding prompts in AI Lecture 7 Demo - The Role and Importance of Prompt Engineering Lecture 8 Best Practices for Effective Prompt Design Lecture 9 Demo - Best practices in prompt design Lecture 10 Challenges and Pitfalls in Prompt Engineering Lecture 11 Demo - Common challenges in prompt engineering Section 3: Hands-on: Building a Prompt Engineering Framework Lecture 12 Setting up the Development Environment Lecture 13 Writing a Basic Prompt Generation Script Lecture 14 Demo - Creating a basic prompt generation script Lecture 15 Customizing Prompts for Specific Use Cases Lecture 16 Demo - Customizing prompts for specific tasks Lecture 17 Demo - Testing and Fine-tuning Your Prompt Models Section 4: Creating Effective Prompts Lecture 18 Exploring Different Types of Prompts Lecture 19 Demo - Understanding different types of prompts Lecture 20 Formulating Precise Prompts for Desired Outputs Lecture 21 Demo - Formulating Precise Prompts for Desired Outputs Lecture 22 Demo - Iterating, Testing, and Refining Prompts Lecture 23 Aligning Prompts with Specific Project Goals Lecture 24 Demo - Using prompt engineering to achieve specific goals Section 5: Optimizing Prompt Generation Lecture 25 Tools and Techniques to Optimize Prompt Generation Lecture 26 Demo - Tools and techniques for optimizing prompt generation Lecture 27 Enhancing Efficiency and Accuracy of Prompts Lecture 28 Demo - Strategies for improving prompt efficiency and accuracy Lecture 29 Ethical Implications in Prompt Engineering Lecture 30 Demo - Considering ethical implications in prompt engineering Lecture 31 Real-world Applications of Optimized Prompts Lecture 32 Demo - Real-world applications of optimized prompt generation Section 6: Advanced Concepts in Generative AI Lecture 33 Exploring Transfer Learning in Generative AI Lecture 34 Demo - Transfer learning in Generative AI Lecture 35 Zero-shot and Few-shot Learning Techniques Lecture 36 Demo - Zero-shot and few-shot learning techniques Lecture 37 Ethical Design in Advanced Prompt Engineering Lecture 38 Demo - Ethical considerations in prompt design Lecture 39 Recent Breakthroughs in Generative AI Research Lecture 40 Demo - Recent advances in Generative AI research Section 7: Applications of Prompt Engineering Lecture 41 Leveraging Prompt Engineering for Content Generation Lecture 42 Demo - Natural language generation for content creation Lecture 43 Automating Code Generation Using Prompts Lecture 44 Demo - Automated code generation using prompts Lecture 45 Using Prompts for Personalized Recommendations Lecture 46 Demo - Personalized recommendation systems with prompt engineering Lecture 47 Enhancing Virtual Assistants with Prompt-driven Responses Lecture 48 Demo - Enhancing chatbots and virtual assistants with prompt design Section 8: Case Studies and Real-world Examples Lecture 49 Case Study: GPT-3 and the Role of Prompt Engineering Lecture 50 Demo - Case study- GPT-3 and prompt engineering Lecture 51 Real-world Implementations of Prompt-based Systems Lecture 52 Demo - Real-world examples of successful prompt-based systems Lecture 53 Lessons from Failed Prompt Engineering Projects Lecture 54 Demo - Lessons learned from failed prompt engineering projects Lecture 55 Future Trends in Generative AI and Prompt Engineering Lecture 56 Demo - Future prospects and trends in Generative AI and prompt engineering Beginners in AI: Individuals with little to no experience in Generative AI who want to explore this growing field.,Aspiring Prompt Engineers: Those interested in learning how to design and optimize effective prompts for AI models.,Developers and Data Scientists: Professionals seeking to enhance their skills in AI by applying hands-on prompt engineering techniques.,Content Creators and Innovators: Creatives looking to leverage Generative AI for content generation, automation, or product innovation. 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Free Download Llm Engineering - Master Ai & Large Language Models (Llms) Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 5.65 GB | Duration: 7h 26m Master Generative AI and Large Language Models (LLMs). Explore and deploy LLM applications, learn fundamental theory. What you'll learn Design and develop a full solution to a given business problem by selecting, training and applying LLMs Compare and contrast the latest techniques for improving the performance of your LLM solution, such as RAG, fine-tuning and agentic workflows Weigh up the leading 10 frontier and 10 open-source LLMs, and be able to select the best choice for a given task Solve problems by applying leading open-source platforms, frameworks and tools, including Hugging Face, Gradio and Weights & Biases State the common AI paradigms, and identify the types of business problems most suitable for each Define fundamental data science concepts around deep learning, including training vs inference, generalizing vs overfitting, and the key ideas behind the NN Describe core concepts such as Generative AI, LLMs and the Transformer Architecture, and discuss what can be achieved with state-of-the-art performance Explain how LLMs work in sufficient detail to be able to train and test them, apply them to new scenarios, and diagnose & fix common issues Implement LLM solutions in Python using frontier and open-source models with both APIs and direct inference Execute code to write documents, answer questions and generate images. Requirements Familiarity with Python. This course will not cover Python basics and is completed in Python. Description Mastering Generative AI and LLMs: An 8-Week Hands-On JourneyAccelerate your career in AI with practical, real-world projects led by industry veteran Ed Donner. Build advanced Generative AI products, experiment with over 20 groundbreaking models, and master state-of-the-art techniques like RAG, QLoRA, and Agents.What you'll learn• Build advanced Generative AI products using cutting-edge models and frameworks.• Experiment with over 20 groundbreaking AI models, including Frontier and Open-Source models.• Develop proficiency with platforms like HuggingFace, LangChain, and Gradio.• Implement state-of-the-art techniques such as RAG (Retrieval-Augmented Generation), QLoRA fine-tuning, and Agents.• Create real-world AI applications, including:• A multi-modal customer support assistant that interacts with text, sound, and images.• An AI knowledge worker that can answer any question about a company based on its shared drive.• An AI programmer that optimizes software, achieving performance improvements of over 60,000 times.• An ecommerce application that accurately predicts prices of unseen products.• Transition from inference to training, fine-tuning both Frontier and Open-Source models.• Deploy AI products to production with polished user interfaces and advanced capabilities.• Level up your AI and LLM engineering skills to be at the forefront of the industry.About the InstructorI'm Ed Donner, an entrepreneur and leader in AI and technology with over 20 years of experience. I've co-founded and sold my own AI startup, started a second one, and led teams in top-tier financial institutions and startups around the world. I'm passionate about bringing others into this exciting field and helping them become experts at the forefront of the industry.Why This Course?• Hands-On Learning: The best way to learn is by doing. You'll engage in practical exercises, building real-world AI applications that deliver stunning results.• Cutting-Edge Techniques: Stay ahead of the curve by learning the latest frameworks and techniques, including RAG, QLoRA, and Agents.• Accessible Content: Designed for learners at all levels. Step-by-step instructions, practical exercises, cheat sheets, and plenty of resources are provided.• No Advanced Math Required: The course focuses on practical application. No calculus or linear algebra is needed to master LLM engineering.Course StructureWeek 1: Foundations and First Projects• Dive into the fundamentals of Transformers.• Experiment with six leading Frontier Models.• Build your first business Gen AI product that scrapes the web, makes decisions, and creates formatted sales brochures.Week 2: Frontier APIs and Customer Service Chatbots• Explore Frontier APIs and interact with three leading models.• Develop a customer service chatbot with a sharp UI that can interact with text, images, audio, and utilize tools or agents.Week 3: Embracing Open-Source Models• Discover the world of Open-Source models using HuggingFace.• Tackle 10 common Gen AI use cases, from translation to image generation.• Build a product to generate meeting minutes and action items from recordings.Week 4: LLM Selection and Code Generation• Understand the differences between LLMs and how to select the best one for your business tasks.• Use LLMs to generate code and build a product that translates code from Python to C++, achieving performance improvements of over 60,000 times.Week 5: Retrieval-Augmented Generation (RAG)• Master RAG to improve the accuracy of your solutions.• Become proficient with vector embeddings and explore vectors in popular open-source vector datastores.• Build a full business solution similar to real products on the market today.Week 6: Transitioning to Training• Move from inference to training.• Fine-tune a Frontier model to solve a real business problem.• Build your own specialized model, marking a significant milestone in your AI journey.Week 7: Advanced Training Techniques• Dive into advanced training techniques like QLoRA fine-tuning.• Train an open-source model to outperform Frontier models for specific tasks.• Tackle challenging projects that push your skills to the next level.Week 8: Deployment and Finalization• Deploy your commercial product to production with a polished UI.• Enhance capabilities using Agents.• Deliver your first productionized, agentized, fine-tuned LLM model.• Celebrate your mastery of AI and LLM engineering, ready for a new phase in your career. Overview Section 1: Week 1 - Build Your First LLM Product: Exploring Frontier Models & Transformers Lecture 1 Day 1 - Mastering LLM Engineering: From Basics to Outperforming GPT-4 in 8 Weeks Lecture 2 Day 1 - Getting Started with Generative AI: First Steps in LLM Project Setup Lecture 3 Day 1 - Building a Web Page Summarizer with OpenAI GPT-4: Instant Gratification Lecture 4 Day 1 - Mastering OpenAI API: Write Code for Frontier Models in Generative AI Lecture 5 Day 2 - Generative AI Course Structure: 8 Weeks to LLM Mastery Lecture 6 Day 2 - Exploring Frontier LLMs: ChatGPT, Claude, Gemini and more Lecture 7 Day 3 - Frontier LLMs: Exploring Strengths and Weaknesses of Top Gen AI Models Lecture 8 Day 3 - ChatGPT vs Other LLMs: Strengths, Weaknesses, and Complementary Models Lecture 9 Day 3 - Claude AI: Exploring Capabilities and Limitations of the Frontier Model Lecture 10 Day 3 - Comparing Gemini AI to Other Frontier Models: Strengths and Limitations Lecture 11 Day 3 - Comparing Frontier LLMs: Command-R Plus, Meta AI, & Perplexity AI Models Lecture 12 Day 3 - Comparing Top AI Models: GPT-4, Claude, and Gemini in Leadership Battle Lecture 13 Day 4 - AI Leadership Battle: Analyzing GPT-4, Claude-3, and Gemini-1.5 Pitches Lecture 14 Day 4 - Gen AI Breakthroughs: Transformer Models & Emergent Intelligence Lecture 15 Day 4 - Tokenization in LLMs: How GPT Processes Text for Natural Language Tasks Lecture 16 Day 4 - Understanding Context Windows: Maximizing LLM Performance and Memory Lecture 17 Day 5 - Implementing One-Shot Prompting with OpenAI for Business Applications Lecture 18 Day 5 - How to Use GPT-4 for JSON Generation in Python: AI-Powered Web Scraping Lecture 19 Day 5 - Building a Full Business Solution with Generative AI and OpenAI's API Lecture 20 Day 5 - Extending Gen AI: Multi-Shot Prompting & Translation Techniques Section 2: Week 2 - Build a Multi-Modal Chatbot: LLMs, Gradio UI, and Agents in Action Lecture 21 Day 1 - Mastering Multiple AI APIs: OpenAI, Claude, and Gemini for LLM Engineers Lecture 22 Day 1 - Streaming AI Responses: Implementing Real-Time LLM Output in Python Lecture 23 Day 1 - How to Create Adversarial AI Conversations Using OpenAI and Claude APIs Lecture 24 Day 1 - AI Tools: Exploring Transformers & Frontier LLMs for Developers Lecture 25 Day 2 - Building AI UIs with Gradio: Quick Prototyping for LLM Engineers Lecture 26 Day 2 - Gradio Tutorial: Create Interactive AI Interfaces for OpenAI GPT Models Lecture 27 Day 2 - Implementing Streaming Responses with GPT and Claude in Gradio UI Lecture 28 Day 2 - Building a Multi-Model AI Chat Interface with Gradio: GPT vs Claude Lecture 29 Day 2 - Building Advanced AI UIs: From OpenAI API to Chat Interfaces with Gradio Lecture 30 Day 3 - Building AI Chatbots: Mastering Gradio for Customer Support Assistants Lecture 31 Day 3 - Build a Conversational AI Chatbot with OpenAI & Gradio: Step-by-Step Lecture 32 Day 3 - Enhancing Chatbots with Multi-Shot Prompting and Context Enrichment Lecture 33 Day 3 - Mastering AI Tools: Empowering LLMs to Run Code on Your Machine Lecture 34 Day 4 - Using AI Tools with LLMs: Enhancing Large Language Model Capabilities Lecture 35 Day 4 - Building an AI Airline Assistant: Implementing Tools with OpenAI GPT-4 Lecture 36 Day 4 - How to Equip LLMs with Custom Tools: OpenAI Function Calling Tutorial Lecture 37 Day 4 - Mastering AI Tools: Building Advanced LLM-Powered Assistants with APIs Lecture 38 Day 5 - Multimodal AI Assistants: Integrating Image and Sound Generation Lecture 39 Day 5 - Multimodal AI: Integrating DALL-E 3 Image Generation in JupyterLab Lecture 40 Day 5 - Build a Multimodal AI Agent: Integrating Audio & Image Tools Lecture 41 Day 5 - How to Build a Multimodal AI Assistant: Integrating Tools and Agents Section 3: Week 3 - Open-Source Gen AI: Building Automated Solutions with HuggingFace Lecture 42 Day 1 - Hugging Face Tutorial: Exploring Open-Source AI Models and Datasets Lecture 43 Day 1 - Exploring HuggingFace Hub: Models, Datasets & Spaces for AI Developers Lecture 44 Day 1 - Intro to Google Colab: Cloud Jupyter Notebooks for Machine Learning Lecture 45 Day 1 - Hugging Face Integration with Google Colab: Secrets and API Keys Setup Lecture 46 Day 1 - Mastering Google Colab: Run Open-Source AI Models with Hugging Face Lecture 47 Day 2 - Hugging Face Transformers: Using Pipelines for AI Tasks in Python Lecture 48 Day 2 - Hugging Face Pipelines: Simplifying AI Tasks with Transformers Library Lecture 49 Day 2 - Mastering HuggingFace Pipelines: Efficient AI Inference for ML Tasks Lecture 50 Day 3 - Exploring Tokenizers in Open-Source AI: Llama, Phi-2, Qwen, & Starcoder Lecture 51 Day 3 - Tokenization Techniques in AI: Using AutoTokenizer with LLAMA 3.1 Model Lecture 52 Day 3 - Comparing Tokenizers: Llama, PHI-3, and QWEN2 for Open-Source AI Models Lecture 53 Day 3 - Hugging Face Tokenizers: Preparing for Advanced AI Text Generation Lecture 54 Day 4 - Hugging Face Model Class: Running Inference on Open-Source AI Models Lecture 55 Day 4 - Hugging Face Transformers: Loading & Quantizing LLMs with Bits & Bytes Lecture 56 Day 4 - Hugging Face Transformers: Generating Jokes with Open-Source AI Models Lecture 57 Day 4 - Mastering Hugging Face Transformers: Models, Pipelines, and Tokenizers Lecture 58 Day 5 - Combining Frontier & Open-Source Models for Audio-to-Text Summarization Lecture 59 Day 5 - Using Hugging Face & OpenAI for AI-Powered Meeting Minutes Generation Lecture 60 Day 5 - Build a Synthetic Test Data Generator: Open-Source AI Model for Business Aspiring AI engineers and data scientists eager to break into the field of Generative AI and LLMs.,Professionals looking to upskill and stay competitive in the rapidly evolving AI landscape.,Developers interested in building advanced AI applications with practical, hands-on experience. 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Free Download MLOps Engineering at Scale Author: Carl Osipov Narrator: n/a English | 2024 | ISBN: 9781617297762 | MP3@64 kbps | Duration: 7h 7m | 583 MB MLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors. You'll learn how to rapidly create flexible and scalable machine learning systems without laboring over time-consuming operational tasks or taking on the costly overhead of physical hardware. Following a real-world use case for calculating taxi fares, you will engineer an MLOps pipeline for a PyTorch model using AWS server-less capabilities. Rapidgator https://rg.to/file/de8b8ed859cc7b00a27484228d2bc712/542uw.rar.html Fikper Free Download https://fikper.com/ELGAGg1VY9/542uw.rar.html Links are Interchangeable - No Password - Single Extraction

epub | 7.24 MB | English| Isbn:9781632405272 | Author: Seth Royal (Editor) | Year: 2016 Description: https://ddownload.com/y3bps9ezugtk https://rapidgator.net/file/eeceae36ad3e40f16a4355afc2b2d06f/

Free Download Cracking the Data Engineering Interview Published 9/2024 Created by Milo Kite MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 102 Lectures ( 3h 55m ) | Size: 3 GB Use SQL, Python, Data Modelling and Project Interview preparation to land your first job in Data Engineering! What you'll learn: To query Data in a Database To write your own scripts in Python The most powerful SQL transformations Python's control flow and conditional logic To sell your project experience effectively To navigate AI's role in Data Strategies for modelling Data in a Database How problems are posed in industry Navigate live-coding interviews calmly Write scalable, professional code Know what role a Data Engineer performs Gain confidence in yourself and experience Set Theory's relation to Data What hiring managers really look for Requirements: No programming experience required, all you need is an email address and an internet connection. All of the tools used can be accessed from your browser. Description: Ready to Launch Your Career in Data Engineering?Whether you're curious about the world of data, a student, looking to change up your career, in a related field, or just looking to sharpen up your skills this course is designed just for you! Cracking the Data Engineering Interview is your gateway to landing a job in one of the fastest-growing, high-demand fields in tech today.Course OverviewCracking the Data Engineering Interview is a beginner-friendly course that takes you step-by-step through everything you need to succeed in your data engineering job hunt. We start with the basics and gradually build your skills, ensuring you're fully equipped to crack any interview. Throughout the course, you'll find loads of bite-sized coding example questions designed to test your skills and remove the scare factor. These exercises are not just practice-they're a built-in study plan, helping you focus on key concepts without the extra effort of planning your own study sessions. What this course DOESN'T include:Downloading any softwareConfusing terminologyWriting code in your terminalLengthy hard to digest lectures Course ContentIntroduction | We'll kick off with an overview of the data engineering landscape, what the role entails, and why it's such a critical function in the age of big data and AI.Data Modelling | Learn the fundamentals of data modelling, including how to structure and organise data in ways that make it accessible, reliable, and easy to analyse.SQL | SQL is the backbone of data engineering. In this module, you'll master the art of writing efficient queries, understanding joins, and optimising databases. You'll also get hands-on practice with exercises that mimic real-world scenarios you'll face in a data engineering role.Projects | This section also teaches you how to effectively present and sell your project experience to hiring managers. You'll learn how to highlight your contributions, explain the impact of your work, and showcase your skills in a way that makes you stand out in interviews.Python | Python is a key tool in the data engineer's toolkit. We'll start from the basics and move into more advanced concepts like data manipulation, scripting, and automation.Start Learning Today!This course is structured to make learning easy and accessible, with no need for complex installations or deep technical know-how to get started. We believe that the best way to learn is by doing, and we're here to support you every step of the way.Get ready to ace your data engineering interview and step into a rewarding career with confidence. Enrol now and take the first step towards your new future!If you have any questions about the content of the course or need any support during the course feel free to reach out to me by email. Who this course is for: This course is designed for programming beginners looking to get their first job in Data Engineering! The most common types are people looking for a career change, graduate students, professionals in related fields, or even Data Engineers looking to round out their experience. 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epub | 26.88 MB | English| Isbn:9781000648300 | Author: David E. Clough, Steven C. Chapra | Year: 2023 Description: https://rapidgator.net/file/5dc80105f8222491676e2dba0c98bd19/ https://ddownload.com/lj8jhr3hmcsx https://nitroflare.com/view/17D2AFBA681EBA0/

Free Download Product Management for Engineering Managers Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz Language: English | Size: 215.92 MB | Duration: 33m 38s Engineering managers have a tough job, guiding engineers to balance business and tech priorities. This course will teach you how to collaborate effectively with product managers to foster a healthy engineering team that builds great products. As an engineering manager, it's tough to balance business and technical priorities. This often shows up when giving your direct reports guidance on how to right-size the fidelity of solutions and code they're writing. In this course, Product Management for Engineering Managers, you'll learn how to speak the language of product to collaborate well with your cross-functional peers. First, you'll explore an overview of product management. Next, you'll discover what a product vision is and why it matters. Finally, you'll learn how to do great stakeholder management so you can increase your influence with your business leaders. When you're finished with this course, you'll have the skills and knowledge of product management needed to collaborate effectively with your product and business stakeholders to foster a healthy engineering team that builds great products. Homepage https://www.pluralsight.com/courses/product-management-engineering-managers TakeFile https://takefile.link/i8sdduo0sh71/qmtnn.Product.Management.for.Engineering.Managers.rar.html Rapidgator https://rg.to/file/a3af5bad2ba106613d5905b8469de586/qmtnn.Product.Management.for.Engineering.Managers.rar.html Fikper Free Download https://fikper.com/TBltWfX1Ov/qmtnn.Product.Management.for.Engineering.Managers.rar.html No Password - Links are Interchangeable

Free Download Overview - Cybersecurity Engineering (ISO/SAE 21434:2021) Published 9/2024 Created by Alexander Walter MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 43 Lectures ( 2h 33m ) | Size: 871 MB Plain and simple clause by clause explanation of ISO/SAE 21434:2021 - Cybersecurity Engineering What you'll learn: Organizational cybersecurity Project dependent cybersecurity management Distributed cybersecurity activities Continual cybersecurity activities Concept Product development Cybersecurity validation Production Operations and maintenance End of cybersecurity support and decommissioning Threat analysis and risk assessment methods Requirements: None Description: The course is divided into two main chapters:- Cybersecurity- ISO 21434Chapter 1: CybersecurityThe chapter provides information on history and basic terms and definitions related to cybersecurity. Also legal aspects are discussed in the chapter.Chapter 2: ISO 21434The chapter includes all chapters of the cybersecurity standard ISO 21434 and explains the most important aspects of the chapters step by step.The following chapters are covered by the course:- Clause 5: Organizational cybersecurity managementThe chapter provides an overview of the most important aspects to be considered at the organizational level. For example the consideration of a cybersecurity policy.- Clause 6: Project dependent cybersecurity managementThe project dependent management includes the definition of responsibilities, a cybersecurity plan and cybersecurity case and more.- Clause 7: Distributed cybersecurity activitiesThis chapter focuses on the supplier interfaces agreement. - Clause 8: Continual cybersecurity activitiesIn this chapter requirements for monitoring of cybersecurity and management of vulnerabilities is described.- Clause 9: ConceptThe concept phase is part of the ISO 21434 V-model and includes the item definition and performance of a threat analysis and risk assessment.- Clause 10: Product developmentThe chapters focuses on the cybersecurity specifications and definition of verification activities.- Clause 11: Cybersecurity validationThe chapter focuses on cybersecurity validation activities.- Clause 12: Production- Clause 13: Operations and maintenance- Clause 14: End of cybersecurity support and decommissioningAt the end you get an overview of the ISO 26262 structure, since the safety standard ISO 26262 is one of the most important references in the ISO 21434. Who this course is for: Cybersecurity responsibles Homepage https://www.udemy.com/course/overview-cybersecurity-engineering-isosae-214342021/ Rapidgator https://rg.to/file/3cc9bb2fa68ce55262aaf8235bc432c4/owwka.Overview..Cybersecurity.Engineering.ISOSAE.214342021.rar.html Fikper Free Download https://fikper.com/zHLYbtLDkF/owwka.Overview..Cybersecurity.Engineering.ISOSAE.214342021.rar.html No Password - Links are Interchangeable

Free Download EssentialSQL - Microsoft Fabric Data Engineering Mastery Published 9/2024 Duration: 7h55m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 3.83 GB Genre: eLearning | Language: English Data Engineering | Microsoft Fabric | Azure Data Factory | Spark | Medallion | Lakehouse | Data Warehouse | SQL | Python What you'll learn Optimize Microsoft Fabric: Learn best practices for efficient data engineering organization. Understand Azure Data Factory: Grasp workflow orchestration for foundational knowledge in data engineering. Apply Data Integration: Utilize principles for end-to-end solutions in comprehensive data engineering. Evaluate Data Transformations: Compare techniques within Microsoft Fabric for informed data processing. Implement Solutions with Azure Data Factory: Leverage it with SQL Data Warehouse for comprehensive data engineering. Develop Solutions with Spark: Create end-to-end solutions for large-scale data processing and analytics. Construct Fabric Data Flows: Tailor flows in Microsoft Fabric for transforming and managing data in Lakehouse. Build Fabric Spark Jobs: Create advanced Spark jobs within Microsoft Fabric for complex data transformations. Establish Data Warehouse: Ingest from Fabric Lakehouse for a scalable and reliable data warehouse. Design ADF Pipelines: Develop Azure Data Factory pipelines for efficient end-to-end data transformations. Create Data Solutions with Dataflows: Construct end-to-end solutions, integrating components for seamless data processing. Apply DevOps for Version Control: Utilize Microsoft DevOps for systematic source code management. Implement Medallion Architecture: Apply advanced principles in Microsoft Fabric for efficient data handling. Requirements Familiarity with SQL and basic programming skills can be beneficial. We'll focus on SQL and Python. I provide to you all the sample you need to complete the case study. Proficiency in programming will be valuable when working with scripting and data transformation tasks Experience in troubleshooting and debugging technical issues will aid in building and troubleshooting Azure Data Factory pipelines. Description Unlock the full potential of data engineering with our comprehensive course on Microsoft Fabric. This hands-on program is designed for individuals seeking to master the latest in data transformation and integration technologies using Microsoft Fabric. Whether you're a data engineer, analyst, or IT professional, this course will equip you with the skills to build robust, scalable data solutions. What You Will Learn Introduction to Microsoft Fabric : Get started with Microsoft Fabric, exploring its core features and capabilities for data engineering. Learn how to set up your workspace and prepare for data ingestion. Medallion Architecture : Understand and implement the Medallion Architecture in Microsoft Fabric. Gain insights into organizing data into Raw, Bronze, Silver, and Gold layers for efficient processing and analysis. Dataflows Gen 2 : Discover the power of Dataflows Gen 2 for transforming and managing data. Learn how to ingest data through various stages, from Raw to Gold, and address common challenges. SQL and Python Integration : Dive into SQL and Python for advanced data transformation and processing. Create pipelines, automate workflows, and leverage SQL queries and PySpark to enhance data management. Visualization and Reporting : Use PowerBI to visualize data and generate insightful reports. Understand how to prepare data for visualization and create meaningful dashboards. End-to-End Solutions : Construct comprehensive end-to-end data engineering solutions. Learn how to integrate dataflows, pipelines, and transformation techniques to build a scalable data architecture. Practical Application : Engage in hands-on exercises with real-world examples, including a Car Sales case study. Work alongside the instructor to implement data engineering solutions and solve practical problems. Course Highlights Hands-On Learning : Experience a practical, "work with me" approach where you'll actively engage with the tools and concepts alongside the instructor. Flexible Learning Path : Start with foundational concepts and advance to complex topics at your own pace. Utilize SQL and Python methods to master different aspects of data transformation. Interactive Exercises : Build and optimize dataflows, create pipelines, and develop comprehensive data models. Address real-world scenarios and troubleshoot common issues. Expert Guidance : Benefit from direct access to course instructors for questions and support. Engage with a community of learners and share insights and solutions. Career Advancement : Enhance your data engineering skills and prepare for roles that require expertise in Microsoft Fabric, SQL, and Python. Gain practical experience that will set you apart in the data engineering field. Who Should Enroll Data Engineers : Professionals looking to enhance their skills in data architecture and processing using Microsoft Fabric. Data Analysts : Individuals seeking to expand their capabilities in data integration and transformation. Database Administrators : Those interested in optimizing data management with Microsoft Fabric. Business Intelligence Professionals : Experts aiming to develop end-to-end solutions for business analytics. Data Scientists : Professionals wanting to strengthen their data engineering skills, especially with large-scale data processing. IT Professionals and Technology Enthusiasts : Individuals interested in the latest Microsoft technologies for data engineering and analytics. Join us to gain hands-on experience with Microsoft Fabric and elevate your data engineering skills to the next level! Note: This course is a good introduction to Fabric and covers many of the topics required for the Azure Data Engineer Associate certification. Check out the preview lesson "Introduction to Microsoft Fabric Data Engineering and Certification Alignment" to see what's covered and what is not. Who this course is for Data Engineers: Professionals responsible for designing, constructing, and maintaining data architecture, databases, and processing systems. Data Analysts: Individuals seeking to expand their data processing and integration skills for comprehensive data analysis. Database Administrators: Those looking to enhance their knowledge of Microsoft Fabric and related tools for optimizing data management. Business Intelligence Professionals: Individuals interested in developing end-to-end solutions for business intelligence and analytics. Data Scientists: Professionals aiming to strengthen their data engineering capabilities, especially in large-scale data processing using technologies like Spark. IT Professionals: Those involved in IT roles looking to specialize in data engineering within the Microsoft ecosystem. Students and Graduates: Individuals pursuing education or recently graduated in fields related to data science, computer science, or information technology. Technology Enthusiasts: Individuals with a keen interest in learning about the latest tools and best practices in the field of data engineering. Professionals Transitioning Careers: Individuals seeking a career change into the field of data engineering or related roles. Anyone Interested in Microsoft Data Technologies: Enthusiasts looking to gain expertise in Microsoft technologies for data engineering and analytics. 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Free Download ChatGPT AI - Artificial Intelligence & AI Prompt Engineering Published 9/2024 Duration: 1h17m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 586 MB Genre: eLearning | Language: English Unlock the Power of ChatGPT: Master AI Prompt Engineering for Content Creation, Automation, and Artificial Intelligence Unlock the Power of ChatGPT: Master AI Prompt Engineering for Content Creation, Automation, and Artificial Intelligence What you'll learn Master AI prompt engineering: Learn how to craft precise prompts for AI tools like ChatGPT to generate accurate and high-quality outputs. Utilize ChatGPT for automation: Discover how to use ChatGPT for automating tasks like content creation, customer service, and more. Develop AI-driven solutions: Understand how to design and implement AI-driven solutions in various fields like business, education, and content creation. Explore the future of AI: Gain insights into the future of artificial intelligence, ethical considerations, and how to leverage AI technologies for growth. Requirements No prior AI experience needed: This course is beginner-friendly and will guide you through all concepts. Interest in AI: A curiosity about artificial intelligence and its applications, especially ChatGPT. Description Are you ready to unlock the full potential of artificial intelligence? In this comprehensive course, ChatGPT AI Artificial Intelligence & AI Prompt Engineering , you'll learn how to harness the power of ChatGPT for various applications, from content creation to automation. This course is designed for beginners and enthusiasts who want to delve into the world of AI. You'll discover the fundamentals of artificial intelligence and gain hands-on experience with prompt engineering-an essential skill for generating high-quality outputs from AI models. Course Outline Section 1: Introduction to AI and ChatGPT Lecture 1: What is Artificial Intelligence? Lecture 2: Overview of ChatGPT Lecture 3: Applications of AI in Everyday Life Section 2: Understanding Prompt Engineering Lecture 4: Introduction to Prompt Engineering Lecture 5: Crafting Effective Prompts Lecture 6: Common Mistakes in Prompt Design Section 3: Using ChatGPT for Various Tasks Lecture 7: Text Generation with ChatGPT Lecture 8: Creative Writing with AI Lecture 9: Automating Customer Support Section 4: Advanced Prompt Techniques Lecture 10: Contextual Prompting Strategies Lecture 11: Multi-Turn Conversations with AI Lecture 12: Leveraging AI for Data Analysis Section 5: Best Practices and Ethical Considerations Lecture 13: Best Practices for AI Usage Lecture 14: Understanding AI Ethics Lecture 15: The Future of AI and Prompt Engineering What You'll Learn Master effective prompt engineering techniques to enhance AI interactions. Utilize ChatGPT for automating repetitive tasks, boosting productivity, and improving customer engagement. Develop innovative AI-driven solutions applicable in business, education, and creative fields. Explore the ethical considerations and future trends of AI to stay ahead in this rapidly evolving landscape. Why Choose This Course? With engaging lectures, practical examples, and real-world applications, you'll gain the skills and confidence to leverage AI in your personal and professional life. Join a community of learners and elevate your understanding of ChatGPT and AI technologies. Enroll now and take the first step towards mastering the future of AI! Who this course is for Beginners in AI: Individuals new to artificial intelligence looking to understand its fundamentals and applications. Content creators: Writers, marketers, and social media managers wanting to leverage AI for content generation and engagement. Tech enthusiasts: Anyone interested in the latest trends in AI and prompt engineering, eager to explore innovative solutions in various fields. Business professionals: Entrepreneurs and business owners seeking to automate tasks and improve efficiency using AI technologies. Homepage https://www.udemy.com/course/chatgpt-ai-artificial-intelligence-ai-prompt-engineering Rapidgator https://rg.to/file/63cac34f7673fcafa37b2ed61025a14d/dnnlp.ChatGPT.AI.Artificial.Intelligence..AI.Prompt.Engineering.rar.html Fikper Free Download https://fikper.com/lzqglv8Rq3/dnnlp.ChatGPT.AI.Artificial.Intelligence..AI.Prompt.Engineering.rar.html No Password - Links are Interchangeable

Free Download Prophecy Data Transformation Copilot for Data Engineering Last updated 5/2024 Created by Mei Long,Richard Marcus,Anya Bida,Maciej Szpakowski MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 114 Lectures ( 5h 20m ) | Size: 1.65 GB Learn Databricks and Spark data engineering to deliver self-service data transformation and speed pipeline development What you'll learn: Learn and design the data lakehouse paradigm for a e-commerce company Hands-on lab environment is provided with this course Implement and deploy a medallion architecture using Prophecy running on Databricks Understand Apache Spark and its best practices with real-life use cases Share and extend Pipeline components with data practitioners and analysts Deploy Pipelines to production and CI/CD and best practices Utilize version control and change management in data engineering Deploy data quality checks and unit tests Requirements: No programming experience needed. You will utilize low-code UI to build a real-life data implementation Description: This course is designed to help data engineers and analysts to build and deploy a cloud data lakehouse architectu using Prophecy's Data Transformation Copilot. It is created with the intention of helping you embark on your data engineering journey with Spark and Prophecy.We will start by staging the ingested data from application platforms like Salesforce, operational databases with CDC transactional data, and machine generated data like logs and metrics. We're going to clean and normalize the ingested tables to prepare a complete, clean, and efficient data model. From that data model, we're going to build four projects creating consumption applications for different real-world use-cases. With each of the projects, you're going to learn something new:We will build a spreadsheet export for your finance department, where we will explore data modeling and transformation concepts. Since the finance department really cares about the quality of data, we're going to also learn about how to setup unit and integration tests to maintain high quality.We will create an alerting system for your operational support team to ensure customer success, where we're going to learn about orchestration best practices.Sales data upload that can be ingested back to Salesforce, where we will explore advanced extensibility concepts that will allows us to create and follow standardized practices.A dashboard directly on Databricks for your product team to monitor live usage. Here we we learn the a lot about observability and data quality.The best part? All of the code that will be building is completely open-source and accessible. You will be able to apply everything your learn here in your real projects.Our entire team of best in-class data engineers and architects with tons of experience from companies like Salesforce, Databricks, and Instagram are going to walk you through, step by step, building out these use-cases. Who this course is for: data engineers, data scientists, data analysts, data architects, data leads, data engineering leads Homepage https://www.udemy.com/course/data-engineering/ Rapidgator https://rg.to/file/73db412d7cd35e09ac8d805ae5d490da/amnfs.Prophecy.Data.Transformation.Copilot.for.Data.Engineering.part1.rar.html https://rg.to/file/488567c34b2d263f70df50f2342674e2/amnfs.Prophecy.Data.Transformation.Copilot.for.Data.Engineering.part2.rar.html Fikper Free Download https://fikper.com/ABkyVp9qm3/amnfs.Prophecy.Data.Transformation.Copilot.for.Data.Engineering.part1.rar.html https://fikper.com/MMuEIMZtvw/amnfs.Prophecy.Data.Transformation.Copilot.for.Data.Engineering.part2.rar.html No Password - Links are Interchangeable

Free Download Advanced Aircraft Engine Engineering Published 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 27m | Size: 1.04 GB Advanced Engine Engineering: From Concept to Validation What you'll learn Develop Skills in Designing and Analyzing Aircraft Engines, from Concept to Validation, Using Advanced Engineering Techniques Understand and Apply the Thermodynamic Cycle in Engines, Optimizing Performance through Multiple Design Points and Integration of Complex Models Implement Strategies for Standardizing Measurements, Ensuring Consistency and Precision in Engine Performance Analysis Analyze the Interaction Between Engine and Aircraft Manufacturers, Focusing on Integration, Development Synergy, and Design Optimization Requirements Interest in Aerospace Technologies and Willingness to Learn Detailed Technical Concepts, from Engine Design to Analysis Description Uncover the Secrets of Aircraft Engine Conceptual Design in a Specialized Course that Combines Advanced Theory with Practical Application, Preparing You to Tackle Real-World Challenges in the Aerospace Industry. Ideal for Engineering Students, Industry Professionals, and Aviation Enthusiasts, This Course Offers a Comprehensive Approach to Mastering Essential Engine Design Principles, from Initial Concept to Final Validation.You Will Learn to Develop Detailed Thermodynamic Models Crucial for Predicting Engine Performance and Efficiency. Additionally, You Will Explore the Optimization of Critical Components Such as Compressors and Turbines, Ensuring That Every Part of the Engine Works in Harmony to Achieve Maximum Performance. A Key Feature of the Course is the Exploration of the Complex Interactions Between Engine and Aircraft Manufacturers, Providing a Strategic Insight into How These Two Worlds Interconnect and Collaborate to Create Cutting-Edge Aerospace Technologies.Throughout the Course, You Will Gain a Deep Understanding of Design Cycles, from the Conceptual Phase to Detailed Development and Validation Testing. We Will Also Cover Model Integration and Station Standardization, Equipping You with the Skills Needed to Apply These Concepts in Real-World Scenarios.This Course Offers an Immersive Experience That Will Prepare You for Success in the Field of Aircraft Engine Engineering. Join Us and Elevate Your Aerospace Career to the Next Level! Who this course is for Aerospace and Mechanical Engineering Students Seeking to Deepen Their Knowledge in Aircraft Engine Design and Analysis. Aerospace Industry Professionals, Including Engineers and Technicians, Looking to Update or Expand Their Skills in Engine Conceptual Design and Systems Integration. Researchers and Academics Interested in Exploring Contemporary Advances and Methodologies in Aircraft Engine Development. Aviation and Technology Enthusiasts Who Wish to Understand the Fundamental Principles and Complexities of Aircraft Engine Design, from Initial Concept to Implementation. Homepage https://www.udemy.com/course/advanced-aircraft-engine-engineering/ Rapidgator https://rg.to/file/281886f5e0d6f5b64551c6bc350f9267/fxhdp.Advanced.Aircraft.Engine.Engineering.part1.rar.html https://rg.to/file/6ce9c014b868d037c8b4c6df1dbd8395/fxhdp.Advanced.Aircraft.Engine.Engineering.part2.rar.html Fikper Free Download https://fikper.com/1guvz53bFp/fxhdp.Advanced.Aircraft.Engine.Engineering.part1.rar.html https://fikper.com/5auHLMobKv/fxhdp.Advanced.Aircraft.Engine.Engineering.part2.rar.html No Password - Links are Interchangeable

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