Znajdź zawartość

Free Download Udemy - SaaS Globalization Primer With GenAI Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 588.45 MB | Duration: 1h 17m If you build it, they will come but only translate it when they arrive What you'll learn Learn why globalization is crucial for SaaS products and the difference between globalization, internationalization (i18n), and localization. Gain insights into preparing software for multiple languages and regions, including best practices for global readiness and avoiding common pitfalls. How to effectively translate and localize content, ensuring that SaaS products are culturally appropriate and resonate with users globally. Gain practical insights through case studies and real-world examples. Understand how GenAI is revolutionizing localization. View key indicators and a checklist of SaaS globalization. Requirements Basic understanding of software development principles. No prior knowledge of globalization or localization required. Description SaaS stands for "Software as a Service". It is a model of delivering software applications over the Internet, where users can access and use the software through a web browser rather than installing and maintaining it on their computers or servers.SaaS facilitates easy access for customers worldwide, eliminating the need for a physical presence to sell products overseas. However, it also makes it easier for customers to switch to competitors with a single click, necessitating an accurate and comprehensive approach to globalization. The SaaS Globalization Primer is designed to equip you with the knowledge and tools needed to improve your software by making it accessible and appealing to users in different languages and cultures. It covers the essential concepts of globalization, internationalization (i18n), and localization (l10n). You'll learn best practices for i18n through practical insights and real-world examples, explore effective l10n strategies, and discover how to manage the complexities of translating and localizing content. This includes using GenAI-powered machine translation and designing a process that continuously improves based on user feedback from different regions, encouraging a proactive and forward-thinking approach to software globalization.Whether you're a product manager, software developer, entrepreneur, or business strategist, you can leverage the principles and practices to succeed in the global SaaS landscape.Course Objectives:Understand the key concepts of globalization, internationalization, and localization.Learn the technical and cultural considerations for making SaaS products globally ready.Develop skills in managing translation and localization processes effectively.Gain practical insights through case studies and real-world examples.Understand how GenAI revolutionize localization. Product Managers, Software Developers, Localization Managers, Business Executives and Entrepreneurs, and anyone interested in SaaS and global markets. Homepage: https://www.udemy.com/course/saas-globalization-primer-with-genai/ [b]AusFile[/b] https://ausfile.com/gm59dtg3z3c1/wpoqi.SaaS.Globalization.Primer.With.GenAI.rar.html Rapidgator https://rg.to/file/df383adc3789d04e6d7d99a44315370c/wpoqi.SaaS.Globalization.Primer.With.GenAI.rar.html Fikper Free Download https://fikper.com/YrfWY028sW/wpoqi.SaaS.Globalization.Primer.With.GenAI.rar.html No Password - Links are Interchangeable

Free Download Master NotebookLM & Perplexity - GenAI to Boost Productivity Published: 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 2h 4m | Size: 1.1 GB Unlock the power of NotebookLM & Perplexity to supercharge research, automate workflows, and drive business growth What you'll learn Master Google NotebookLM to dramatically enhance productivity and research efficiency. Generate professional-quality AI-powered podcasts and interactive audio summaries effortlessly. Develop real-world projects, such as AI-powered legal counseling tools and content-rich applications. Utilize Perplexity AI for quick, accurate, and smarter answers to complex questions, significantly reducing research time. Integrate Perplexity API into your Python projects to create sophisticated, AI-driven applications. Learn to combine NotebookLM and Perplexity seamlessly for maximum impact in professional and academic settings. Join this hands-on session exploring NotebookLM and Perplexity, uncovering top use cases to boost your productivity in both business and educational settings. Requirements No prior knowledge is required. A free Google account. For the Perplexity API with Python section, a credit card is required. Description Feeling overwhelmed by information overload and rapid AI advances? Discover how powerful generative AI tools like NotebookLM and Perplexity can revolutionize your workflow.This practical course on Google's NotebookLM and Perplexity helps business leaders and professionals boost research efficiency, automate tedious tasks, and integrate AI seamlessly-giving you more time for strategic, high-value work.Why This Course?Cut Through Research Chaos: Instantly summarize documents, extract insights, and create customized audio Overviews with Google's NotebookLM.Instant Answers & Insights: Quickly get accurate, cited answers with Perplexity AI.Automate Workflows: Automate routine tasks-emails, reports, marketing copy-with the latest GenAI tools.AI Integration Strategy: Seamlessly integrate AI solutions into your business operations.What You'll Master:NotebookLM: Effortlessly organize research, create summaries and audio Overviews (podcasts), and speed up report writing.Perplexity AI: Get instant, accurate answers, integrate the Perplexity API with Python, and build powerful AI-driven applications.Real-world Projects: Develop practical AI applications, automate business workflows, and boost productivity.Ideal For:Business professionals wanting AI-enhanced productivity.Students aiming to accelerate research and learning.Developers integrating GenAI into their projects.Imagine: Instead of evenings overloaded with data, let AI filter information and draft insights in minutes. Automate tasks that previously took hours and unlock more time for innovation.Take the Next StepThe future belongs to those who leverage AI effectively. Don't get left behind as competitors embrace these transformative tools.Enroll today to instantly transform your productivity and innovation with NotebookLM, Perplexity, Python API, and cutting-edge GenAI tools. Let's revolutionize your workflow-together! Who this course is for Business professionals looking to leverage NotebookLM and Perplexity to boost productivity and decision-making. Students eager to master powerful generative AI tools for research, studying, and academic projects. Developers seeking practical knowledge to integrate Perplexity API into their Python-based applications. Content creators aiming to innovate with interactive, engaging AI-generated media. Anyone interested in rapidly improving their skills with NotebookLM and Perplexity AI to gain a competitive edge. Homepage: https://www.udemy.com/course/master-notebooklm-perplexity-genai-to-boost-productivity/ [b]AusFile[/b] https://ausfile.com/xp79906ltlcf/aklac.Master.NotebookLM..Perplexity.GenAI.to.Boost.Productivity.part1.rar.html https://ausfile.com/4gb2pacnegpj/aklac.Master.NotebookLM..Perplexity.GenAI.to.Boost.Productivity.part2.rar.html Rapidgator https://rg.to/file/2dee6f3eb0cd4374359f703e92ed612c/aklac.Master.NotebookLM..Perplexity.GenAI.to.Boost.Productivity.part1.rar.html https://rg.to/file/1908b5d733ab9f61c024d820aaed74b7/aklac.Master.NotebookLM..Perplexity.GenAI.to.Boost.Productivity.part2.rar.html Fikper Free Download https://fikper.com/BfCG8rr4AJ/aklac.Master.NotebookLM..Perplexity.GenAI.to.Boost.Productivity.part1.rar.html https://fikper.com/Aw6c8vs1Xo/aklac.Master.NotebookLM..Perplexity.GenAI.to.Boost.Productivity.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - GenAI and Predictive AI Architecture Published: 3/2025 Created by: Edcorner Learning MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Expert | Genre: eLearning | Language: English | Duration: 25 Lectures ( 3h 22m ) | Size: 1 GB Explore The Generative AI & Predictive AI Architectures, Core Components, Layers, Model Types & Use Cases What you'll learn Foundations of Generative AI & Predictive AI Understand the key components and layers within Generative AI and Predictive AI architectures. Learn the differences between traditional AI, Generative AI, and Predictive AI and how to select the right approach. Analyze enterprise AI architecture and its application Explore various types of Generative AI models, including GANs, VAEs, Transformers, and Diffusion models. Discover the best practices for using Generative AI in business applications. Compare Conversational AI vs. Generative AI to understand chatbot and AI assistant implementations. Explore over 40+ real-world use cases of Generative AI across industries. Evaluate the top Generative AI tools and platforms, including OpenAI's GPT models, Google's Bard, Stability AI, and more. Learn about popular Generative AI models and their key differentiators. Understand the differences between Large Language Models (LLMs) and Generative AI and when to use each. Learn the layers of Predictive AI architecture and how data is processed for forecasting and decision-making. Explore various Predictive AI models, such as regression models, decision trees, neural networks, and time series forecasting. Understand how Predictive AI works, including data ingestion, model training, and prediction generation. Gain knowledge on how to implement Predictive AI in an organization Compare Generative AI vs. Predictive AI applications to determine their respective strengths in different scenarios. Explore the Generative AI Monitoring Architecture Learn how Predictive AI Monitoring Architecture works to enhance model accuracy, reduce drift, and optimize decision-making. Requirements Basic Knowledge of AI No advanced programming knowledge is required Description The rapid advancements in artificial intelligence (AI) have led to the rise of two transformative branches: Generative AI and Predictive AI. This comprehensive course explores their architectural foundations, key components, and practical applications in enterprise environments. Designed for AI professionals, data scientists, and business leaders, this course provides a deep dive into how these two AI paradigms work, their unique advantages, and their role in shaping the future of automation and decision-making.The course begins with an in-depth exploration of Generative AI Architecture & Key Components, where learners will understand the essential layers within Generative AI and how various models, such as GANs, VAEs, and diffusion models, generate new content. We will examine Types of Generative AI Models and their outputs, followed by discussions on best practices for leveraging Generative AI effectively in different domains. A comparative analysis of Traditional AI vs. Generative AI and Conversational AI vs. Generative AI will provide clarity on when to adopt these technologies. Enterprise implementation strategies will be covered in Enterprise Generative AI Architecture Layers & Components, along with real-world examples of Top 40+ Generative AI Use Cases and the Top 7 Most Popular Generative AI Tools and Platforms.Moving to Predictive AI, the course explores Predictive AI Architecture, including its layers and models, and delves into how Predictive AI works in real-world applications. We will discuss differences in architecture, purpose, and implementation compared to Generative AI, helping professionals make informed decisions when deploying AI solutions. Practical sessions on implementing Predictive AI in organizations will guide learners through real-world case studies.Finally, the course examines AI monitoring frameworks, focusing on Generative AI Monitoring Architecture and Predictive AI Monitoring Architecture to ensure AI systems remain efficient, ethical, and reliable. By the end of this course, parti[beeep]nts will have a robust understanding of how to choose between Large Language Models (LLMs) and Generative AI, as well as the fundamental distinctions between Generative AI and Predictive AI applications. Who this course is for AI & Machine Learning Professionals Data Scientists & Analysts AI engineers, data scientists, and ML practitioners AI developers Data analysts C-level executives, AI strategists, and product managers Innovation leaders seeking to integrate Generative AI and Predictive AI into business models Professionals responsible for AI adoption and governance within enterprises. Software Engineers & AI Developers Academic Researchers & AI Enthusiasts Homepage: https://www.udemy.com/course/genai-and-predictive-ai-architecture/ [b]AusFile[/b] https://ausfile.com/7azke1x39y7v/bksfe.GenAI.and.Predictive.AI.Architecture.part1.rar.html https://ausfile.com/k7pom47ob02r/bksfe.GenAI.and.Predictive.AI.Architecture.part2.rar.html Rapidgator https://rg.to/file/5cd1af9c2d12c75cc9852a5b0f7bcde5/bksfe.GenAI.and.Predictive.AI.Architecture.part1.rar.html https://rg.to/file/694c1673ac661fc3c3d1ee3a96ca1d90/bksfe.GenAI.and.Predictive.AI.Architecture.part2.rar.html Fikper Free Download https://fikper.com/2APFoReZSM/bksfe.GenAI.and.Predictive.AI.Architecture.part1.rar.html https://fikper.com/cDpmIGPqeM/bksfe.GenAI.and.Predictive.AI.Architecture.part2.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Building an AI Council That Drives GenAI Adoption and Innovation Released 03/2025 With Jim Sterne MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 51m 8s | Size: 97 MB This course teaches you how to carefully drive AI adoption and innovation in your organization-no technical expertise required. This is modern change management. Course details In this course, learn how you can drive AI adoption and innovation in your organization-no technical expertise required. Instructor Jim Sterne shares best practices for establishing and running an effective AI council. Learn to assemble a team that represents key stakeholders across the org, how to develop ethical guidelines for AI use, and how to implement effective governance structures that drive AI adoption across the company. Bring in generative AI in a controlled way that carefully encourages innovation. This course is a playbook for establishing an internal AI Council to track the rampant advances in generative AI, provide direction on policies, guidelines, and training, and act as a clearing house for best practices and collective learnings. Homepage: https://www.linkedin.com/learning/building-an-ai-council-that-drives-genai-adoption-and-innovation Fileaxa https://fileaxa.com/o9ng0e02j0ln/pxxel.Linkedin..Building.an.AI.Council.That.Drives.GenAI.Adoption.and.Innovation.rar TakeFile https://takefile.link/v4iymsbcjfsj/pxxel.Linkedin..Building.an.AI.Council.That.Drives.GenAI.Adoption.and.Innovation.rar.html Rapidgator https://rg.to/file/6c111dd64329d457b68ddb91ea8873ed/pxxel.Linkedin..Building.an.AI.Council.That.Drives.GenAI.Adoption.and.Innovation.rar.html Fikper Free Download https://fikper.com/6m3fE3SFua/pxxel.Linkedin..Building.an.AI.Council.That.Drives.GenAI.Adoption.and.Innovation.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Amazon Q in Connect - GenAI Contact Center Released 03/2025 With Wendy Wong MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 16m 38s | Size: 268 MB Learn how to create personalized customer experience (CX) and leverage an AI-powered contact center using Amazon Q in Connect. Course details AI stands to revolutionize the world of customer service, and contact centers are already following suit. In this course, instructor Wendy Wong shows you how to create personalized customer experience (CX) and leverage AI to understand and resolve customer inquiries using Amazon Q in Connect, the generative AI-powered assistant for customer service that delivers customers and agents the information they need to solve issues in real time quickly with ease. Transform your contact center with the power of AI using prompts in natural language to extract data insights and summarize customer calls. By the end of this course, you'll be prepared to leverage Amazon Q in Connect to help deliver an omnichannel digital experience and increase agent productivity. Homepage: ?https://www.linkedin.com/learning/amazon-q-in-connect-genai-contact-center TakeFile https://takefile.link/q9yc68i2b57e/waxer.Linkedin..Amazon.Q.in.Connect.GenAI.Contact.Center.rar.html Rapidgator https://rg.to/file/c244fd3e926f0646e0778ed6795e8eb2/waxer.Linkedin..Amazon.Q.in.Connect.GenAI.Contact.Center.rar.html Fikper Free Download https://fikper.com/VIL11ohIah/waxer.Linkedin..Amazon.Q.in.Connect.GenAI.Contact.Center.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Learn Databricks GenAI Released 03/2025 With Lynn Langit MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 11m 10s | Size: 226 MB Explore the world of Generative AI with Databricks as you learn about prompt engineering, vector search, RAG patterns, and model tuning. Course details In this detailed course, cloud architect and experienced technical educator Lynn Langit explores Generative AI with Databricks. Discover how to use prompt engineering in Databricks AI and BI to effectively query data with AI prompts. Learn to implement and set up Vector Search to enhance your GenAI applications. Understand the Retrieval-Augmented Generation (RAG) pattern and its integration to boost your AI projects with your data. Get hands-on with model tuning, including foundation model training and fine-tuning with Hugging Face transformers. Gain the skills you need to harness AI for data queries, implement advanced search techniques, and fine-tune AI models. This course empowers you to unlock the power of Databricks and elevate your data-driven decision-making capabilities. Homepage: https://www.linkedin.com/learning/learn-databricks-genai TakeFile https://takefile.link/xfurrobg4cos/yxbmb.Linkedin..Learn.Databricks.GenAI.rar.html Rapidgator https://rg.to/file/7bd023bd67d14ce57718840ca7cc8fa2/yxbmb.Linkedin..Learn.Databricks.GenAI.rar.html Fikper Free Download https://fikper.com/1P9Vrjynwl/yxbmb.Linkedin..Learn.Databricks.GenAI.rar.html : No Password - Links are Interchangeable

Free Download Udemy - GenAI For Kids Published: 2/2025 Created by: Gaurav Kumar MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 109 Lectures ( 8h 25m ) | Size: 7 GB Unlocking Creativity and Critical Thinking: A Fun Dive into Generative AI for K12 Students! What you'll learn Learn different Gen AI techniques for getting better at school Curriculum and projects Learn the Prompting Technique for Better Results Learn to Enhance Memory using Generative AI Leran Innovation by the use of Generative AI and Lateral Thinking Principles Requirements No programming experience needed. Description In the "Exploring Generative AI" course, I teach a comprehensive curriculum designed to empower K12 students with cutting-edge knowledge and practical skills. This course starts with an engaging introduction to Generative AI, where students explore ChatGPT, learn effective interaction techniques, and even dive into custom GPT models and AI-powered visuals. Through hands-on exercises, they gain real-world experience with OpenAI Playground and advanced AI tools.The Communication module enhances students' public speaking, persuasive writing, and active listening skills, offering opportunities to practice through debates and role-playing. Memory techniques such as flashcards, mnemonics, visualization, and advanced strategies like the Loci Method and Dominic System are covered to boost academic performance.We delve into Everyday Productivity, teaching students how to manage study schedules, meal planning, focus sessions, and travel efficiently. The Presentation and Creatives module covers design principles, storytelling, and creating impactful visuals. Students also get hands-on with Robotics, learning coding, circuit design, and debugging using platforms like Replit.For those aiming for excellence, Competition Readiness and Research and Analytical Skills modules build critical thinking and problem-solving abilities. The Model United Nations (MUN) segment focuses on speechcraft, research, diplomacy, and role-playing, equipping students with leadership and negotiation skills.Finally, the Lateral Thinking module introduces innovative approaches to problem-solving, encouraging creative thinking and flexibility. This holistic course ensures students are not only tech-savvy but also well-rounded individuals, ready to excel in academic and real-world scenarios. Who this course is for School kids from 6th to 12th grade Homepage: https://www.udemy.com/course/genai-for-kids/ Rapidgator https://rg.to/file/2207e9f4e6924014dad9e14b601b33fd/urnpf.GenAI.For.Kids.part1.rar.html https://rg.to/file/b25bad858ebd835d4f3e28923d43bf05/urnpf.GenAI.For.Kids.part2.rar.html https://rg.to/file/aeb02cd885bb479782ca74cbd62f0847/urnpf.GenAI.For.Kids.part3.rar.html https://rg.to/file/13b7737ce5c4b356aca36d398b3824c2/urnpf.GenAI.For.Kids.part4.rar.html https://rg.to/file/42c7527f5b6f1f6bac89ffd70393510b/urnpf.GenAI.For.Kids.part5.rar.html https://rg.to/file/ce5c3e35ce14947d2e612dd322b35208/urnpf.GenAI.For.Kids.part6.rar.html https://rg.to/file/63fa13a048e50d63c900280cb48e5261/urnpf.GenAI.For.Kids.part7.rar.html https://rg.to/file/d9dc01bb2bc8c51c76c6c5b28ee53153/urnpf.GenAI.For.Kids.part8.rar.html Fikper Free Download https://fikper.com/52aU8dkFaW/urnpf.GenAI.For.Kids.part1.rar.html https://fikper.com/PSD8fryruS/urnpf.GenAI.For.Kids.part2.rar.html https://fikper.com/QNBYEfD0y6/urnpf.GenAI.For.Kids.part3.rar.html https://fikper.com/2nALje68qa/urnpf.GenAI.For.Kids.part4.rar.html https://fikper.com/muoeRJLqFm/urnpf.GenAI.For.Kids.part5.rar.html https://fikper.com/wvg88TiUd7/urnpf.GenAI.For.Kids.part6.rar.html https://fikper.com/ck1rCY3WiD/urnpf.GenAI.For.Kids.part7.rar.html https://fikper.com/6oUqsoWqPj/urnpf.GenAI.For.Kids.part8.rar.html : No Password - Links are Interchangeable

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

Free Download DeepSeek Comprehensive Guide - GenAI, AI Agents, Monetization Published: 2/2025 Created by: Luca Hao MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitles | Duration: 41 Lectures ( 3h 27m ) | Size: 1.6 GB Master DeepSeek: Supercharge Productivity, Content Creation, and Automation | Build AI Agents | Monetize with 24+ Business What you'll learn Master DeepSeek's key features and capabilities, comparing its performance with tools like ChatGPT and Claude for optimized use. Leverage DeepSeek for efficient content creation, marketing, and social media management to drive business growth and engagement. Utilize DeepSeek for business automation, enhancing productivity through AI-powered agents for customer support, data insights, and project management. Understand the fundamentals of prompt engineering and apply advanced prompting techniques to improve AI performance and tailor content creation. Explore profitable opportunities by monetizing DeepSeek through digital products, AI agents, and subscription-based business models. Gain a deep understanding of the ethical implications of AI automation, fostering responsible use of DeepSeek in various industries. Requirements No prerequisites as Deepseek is a tool anyone can access and use immediately. Description In This Comprehensive DeepSeek Guide, You'll Learn How To:Master DeepSeek Basics:Navigate the DeepSeek platform and understand its unique features and capabilities.Set up your DeepSeek account and get started with models, APIs, and prompts.Master essential commands and functions to quickly launch your first project.Leverage DeepSeek for Content Creation, Marketing, and Social Media:Write compelling articles, blogs, and marketing copy using DeepSeek's powerful tools.Craft social media content and explore DeepSeek's potential for SEO and brand strategy.Build a content strategy that drives engagement and growth.Automate Business and Productivity with DeepSeek:Use DeepSeek to automate customer support and streamline workflows with AI agents.Leverage DeepSeek for data analysis, task management, and project collaboration.Develop business automation plans for various industries such as finance.Build and Monetize AI Agents:Create custom AI agents to automate tasks, manage workflows, and solve business challenges.Integrate DeepSeek with tools like Zapier and Slack for advanced applications.Learn to market and sell AI agents as a service, building scalable AI solutions for clients.Unlock Advanced Prompt Engineering:Master the art of prompt engineering, learning advanced techniques like Chain of Thought and Few-Shot Learning.Access 1000+ prompts designed for content creation, social media, SEO, and more.Optimize prompts to improve AI performance and tailor them to specific business needs.Monetize DeepSeek:Learn how to sell AI agents as a service, create digital products like templates and eBooks, and explore subscription-based business models.Discover over 25 business ideas you can start today using DeepSeek's powerful AI capabilities.Build passive income streams by leveraging DeepSeek for automated systems in SEO, content creation, and social media management.Who this course is for :Professionals: Save time and increase productivity with DeepSeek's powerful automation tools.Entrepreneurs: Scale your business with AI-powered automation and innovative strategies.Freelancers: Offer in-demand AI services, including AI agents and content creation.AI Enthusiasts: Dive into practical applications of AI and become an expert in using DeepSeek for real-world projects.What You'll Get:Step-by-Step Guides: Learn how to build and monetize AI agents and develop actionable skills.Real-World Applications: Practical exercises and examples to apply what you learn.1000+ Advanced Prompts: Ready-to-use prompts for content, marketing, and business automation.Don't Wait-Start Building Your AI Future Now!Join thousands of students and take the first step towards mastering DeepSeek and transforming your career with AI. Whether you want to boost productivity, create AI-driven solutions, or build a new income stream, this course is your ultimate guide.Enroll now and let's get started!Thank you!- Luca, Prin[beeep]l AI Architect | Software Enginee Who this course is for AI enthusiasts who are eager to dive deep into one of the most advanced AI tools and stay ahead of the curve. Professionals seeking to enhance their workflow efficiency, automate tasks, and maximize productivity with cutting-edge AI technology. Entrepreneurs looking to scale their businesses by leveraging AI agents for automation and data-driven insights. Freelancers aiming to offer high-demand AI-powered services such as content creation, marketing, and automation to clients. Digital marketers interested in using AI for SEO, content strategy, and social media growth. Individuals looking to generate passive income through AI-driven solutions and monetization opportunities with tools like DeepSeek. Homepage: https://www.udemy.com/course/deepseek-comprehensive/ Rapidgator https://rg.to/file/cacccbabc1ebdc3475f310c2d4109d5e/zsccy.DeepSeek.Comprehensive.Guide.GenAI.AI.Agents.Monetization.part1.rar.html https://rg.to/file/dd833807f6fcf58a7e5aaffe1a5e9838/zsccy.DeepSeek.Comprehensive.Guide.GenAI.AI.Agents.Monetization.part2.rar.html Fikper Free Download https://fikper.com/pDpkUuUD0K/zsccy.DeepSeek.Comprehensive.Guide.GenAI.AI.Agents.Monetization.part1.rar.html https://fikper.com/0vefmP2pVQ/zsccy.DeepSeek.Comprehensive.Guide.GenAI.AI.Agents.Monetization.part2.rar.html : No Password - Links are Interchangeable

Free Download Quantization for GenAI Models by Start-Tech Academy Published 10/2024 Created by Start-Tech Academy MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 34m ) | Size: 807 MB Unlock the power of model optimization! Learn how to apply quantization and make your GenAI models efficient with Python What you'll learn Understand model optimization techniques: Pruning, Distillation, and Quantization Learn the basics of data types like FP32, FP16, BFloat16, and INT8 Master downcasting from FP32 to BF16 and FP32 to INT8 Learn the difference between symmetric and asymmetric quantization Implement quantization techniques in Python with real examples Apply quantization to make models more efficient and deployment-ready Gain practical skills to optimize models for edge devices and resource-constrained environments Requirements Basic Python knowledge is recommended, but no prior AI experience is required. Description If you are a developer, data scientist, or machine learning enthusiast who wants to optimize and deploy efficient AI models, this course is for you. Do you want to make your models faster and more resource-efficient while maintaining performance? Are you looking to learn how to apply quantization techniques for better model deployment? This course will teach you how to implement practical quantization techniques, making your models lean and deployable on edge devices.In this course, you will:Learn the core concepts of Quantization, Pruning, and Distillation.Understand different data types like FP32, FP16, BFloat16, and INT8.Explore how to convert FP32 to BF16 and INT8 for efficient model compression.Implement symmetric and asymmetric quantization in Python with real-world applications.Understand how to downcast model parameters from FP32 to INT8 for deployment.Gain hands-on experience with Python-based quantization, making your models suitable for mobile and IoT devices.Why learn quantization? Quantization allows you to reduce the size and computational load of models, making them suitable for resource-constrained devices like smartphones, IoT devices, and embedded systems. By mastering quantization, you can ensure your models are faster, more energy-efficient, and easier to deploy while maintaining accuracy.Throughout the course, you'll learn to implement quantization techniques and optimize your models for real-world applications. This course provides the perfect balance of theory and practical application for making machine learning models more efficient.By the end of the course, you'll have a deep understanding of quantization, and the ability to optimize and deploy efficient models on edge devices. Ready to optimize your AI models for efficiency and performance? Enroll now and start your journey! Who this course is for Beginners in machine learning looking to learn practical model optimization techniques like quantization AI professionals and students wanting to optimize models for deployment on resource-constrained devices Homepage https://www.udemy.com/course/quantization/ Screenshot Rapidgator https://rg.to/file/650f02e9b5b1ad8b23a1e82b4f7e0043/jdifw.Quantization.for.GenAI.Models.rar.html Fikper Free Download https://fikper.com/UD5gJmXWhS/jdifw.Quantization.for.GenAI.Models.rar.html No Password - Links are Interchangeable

Free Download Master Azure Artificial Intelligence (AI, ML, GenAI) Published 10/2024 Created by Freddy Ayala MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 39 Lectures ( 5h 20m ) | Size: 2.2 GB Become a Master of Azure AI Services (Speech, Visio, OpenAI, AI Studio, Promptflow) and Get Certified (AI-102) What you'll learn Navigate Azure's AI services to create smart app features. Apply AI with hands-on Azure-based projects. Implement generative AI for dynamic content. Deploy robust and scalable AI apps on Azure. Integrate their applications into an enterprise lanscape taking into account gouvernance and security Requirements Basic Programming Knowledge: Familiarity with a programming language, preferably C# or Python, used within Azure's context. Azure Fundamentals: An understanding of core Azure services and navigating the Azure portal. Development Environment: Access to a computer with internet connectivity, capable of running Azure's cloud services. Azure Subscription: While a free tier may be sufficient for starters, a paid subscription could be required for more advanced features. Description Embark on a journey to become a Microsoft AI Certified professional with our comprehensive course. Designed for aspiring Azure AI Engineers, this program equips you for the AI-102 certification while empowering you to build impactful AI solutions. Through hands-on learning, you'll master creating intelligent applications using Azure's powerful AI capabilities.What You'll Learn:Introduction to Azure and AI:Gain foundational knowledge of Azure and its AI services.Computer Vision Solutions:Develop image analysis, facial recognition, custom vision, and video analysis skills using Azure AI Vision.Natural Language Processing (NLP):Learn text analysis, translation, question answering, and conversational app building.Explore custom classification and speech recognition.Knowledge Mining:Create intelligent search solutions and knowledge stores using custom skills.Document Intelligence:Understand Azure's Document Intelligence Service with prebuilt and custom models.Generative AI with Azure OpenAI:Get started with Azure OpenAI Service and learn app development, prompt engineering, and data utilization.AI Studio:Explore AI Studio architecture, setup, deployment, and integration with Azure.PromptflowArchitecture and Security Best practicesCertification Preparation:Equip yourself with the skills needed for the Microsoft Certified: Azure AI Engineer Associate exam.Course Highlights:Azure AI-Centric Curriculum: Specialize in using Azure AI services for computer vision, NLP, knowledge mining, document intelligence, and generative AI.Interactive Labs: Gain hands-on experience with image analysis, language processing, and AI service deployment.Up-to-Date Learning: Prepare for the AI-102 certification with content updates reflecting current exam requirements.End-to-End Solution Development: Focus on building comprehensive and innovative AI applications.AI Studio Exploration: Delve into AI Studio architecture, setup, and deployment for creating intelligent solutions.Who This Course Is For:Developers aiming to build AI-driven applications using Azure AI.AI enthusiasts eager to deepen their Azure AI knowledge.Candidates for the Microsoft Certified: Azure AI Engineer Associate certification seeking hands-on learning.Prerequisites:Experience with Python programming.Basic understanding of Azure services.Your Instructor:Freddy is a well know worlwide Microsoft Subject Matter Experts skilled in AI technologies and Python that has contributed to the Microsoft AI Community. Here is a list of some of his contributions:Basic OpenAI end-to-end chat reference architectureBaseline OpenAI end-to-end chat reference architectureAzure OpenAI chat baseline architecture in an Azure landing zoneAI Studio End-to-End Baseline Reference ImplementationAnd many othersCertification Path:AI-102 Exam Preparation: Gain the knowledge needed to pass the Azure AI Engineer Associate exam.Skills You'll Develop:Planning and managing Azure AI solutions.Deploying services for complex decision-making.Building image recognition capabilities.Creating NLP-based chatbots and services.Engineering document intelligence solutions.Innovating with Python for generative AI.Course Outcome:Complete the course ready to pass the Microsoft Azure AI Engineer Associate exam, armed with the expertise to lead AI initiatives. Become proficient in driving AI projects and leveraging Azure and Python technologies.Enrollment:Enroll now to advance your career. Become a Microsoft AI Certified professional, bringing intelligent solutions to life. Sign up today and shape the future of AI application development. Who this course is for Software Developers: Enhance apps with Azure AI. Data Enthusiasts: Dive into AI model integration. IT Professionals: Master AI deployment on Azure. Recent Graduates: Begin your AI development journey. Tech-savvy Entrepreneurs: Innovate with AI features. Homepage https://www.udemy.com/course/master-azure-ai/ Screenshot Rapidgator https://rg.to/file/6acb3f7c5f7bf066feb3207fcaa9bdbd/pwnwp.rar.html Fikper Free Download https://fikper.com/QQEfMpaSSV/pwnwp.rar.html No Password - Links are Interchangeable

Free Download GenAI Fundamentals for UX Designers + Researchers Published 10/2024 Created by Joe Natoli MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 29 Lectures ( 2h 47m ) | Size: 3.12 GB Learn the key concepts and components to harness GenAI for UX design - and lead AI product innovation efforts. What you'll learn Learn core principles of responsible GenAI design that ensure our products serve all users equally + equitably. Success factors unique to Machine Learning (ML) products that UX + Product Designers and their teams should adopt Guidance on research to determine what kinds of problems are best solved by AI, and where human control should remain central. Determining when AI features are appropriate for users - and when they aren't Identifying when Automation (AI does the task for users) or Augmentation (help them do it better) is more appropriate. Designing the reward function and appropriately considering the balance between false positives and false negatives. Essential factors to consider when evaluating the reward function. How to weigh necessary, unavoidable tradeoffs between precision and recall, which is key to shaping an AI user experience. Designing for fairness and inclusion, from objectives to datasets to guidance on bias testing. Designing for generative variability: how do we present multiple, varied outputs to users - and how do we guide them in selecting the best one? Designing for multiple outputs: how do we help users filter and highlight differences between outputs? Designing for imperfections: how do we empower users to manage + mitigate imperfections and designing with contextual sensitivity? Designing for confidence: how do we design confidence scoring to properly evaluate output quality and increase user trust? Rules and examples for applying confidence scores. Designing for co-creation: how to we design co-creation processes where both the user and the AI can make adjustments? Designing for generic controls: using "temperature" to control the number of outputs and the degree of variability in those outputs. Designing for domain-specific controls, such as encoder-decoder models, semantic sliders and prompt engineering. Designing for prompt engineering: enabling and guiding users to effectively use multiple types of conversational prompts. Designing for exploration: incorporating flexibility, feedback, transparency and error handling/expectation management. Designing for choice, feedback, transparency + safety: centering users as active, empowered parti[beeep]nts in the creation process. Designing for mental models: orienting users to generative variability, teaching effective use and teaching the AI about the user. Designing for explanation, understanding + trust: providing clear rationales for outputs, using friction to curb over-reliance and showing imperfections. Designing against harm: understanding the critical ways irresponsible AI design can harm people. Designing against hazardous outputs: discrimination, exclusion, toxicity, misinformation, deep fakes, IP theft and more. Mitigating harm with a Value-Sensitive Design (VSD) process, integrated with an Agile or Lean development process. Requirements None. GenAI is stil extremely new to the world of UX, so this fundamentals course is meant to get you on solid ground fast, no matter your experience. Description Protect and grow your career: Learn to design GenAI-enabled productsThe UX and Product design landscape is evolving-and AI is leading the charge. If you're a designer, UXer, or product developer, you can't afford to be left behind. Generative AI is not just a buzzword; it's becoming the backbone of the next generation of user experiences. And without a deep understanding of how to design AI-powered products, your skill set risks becoming obsolete.This course is for you if you want to:Stay relevant in an industry that's rapidly integrating AI into every aspect of product development and feature sets.Be the asset your employer relies on-not the UXer or designer left off key projects because you lack the necessary skills.Lead the future of UX and design rather than have it dictated to you by engineers and product managers.Why you must start learning the fundamentals of GenAI product design nowAI isn't just an optional add-on anymore. It's the next fundamental shift in product design-just like when UX and UI became indispensable. Here's the reality:Employers want designers who understand how to design user-centered GenAI experiences that are useful, usable, valuable, and trustworthy. Without this skill, your job security and opportunities will shrink.Product improvement initiatives and AI integration projects are happening in every major company, from simple voice and chatbot interfaces to workflow-based conversational experiences. The people who know how to design these experiences are the ones who will be chosen for leadership roles.AI is the new frontier in UX and product design. Just as front-end coding knowledge became essential for UXers, understanding emerging design trends for GenAI - and how to design and evaluate AI-enabled products - is the next career progression.If you don't understand AI-enabled design, you won't be part of these key projects. Your value will diminish-both to your current employer and in the eyes of potential future employers.What you'll learn in this courseMaster the fundamentals of designing AI-powered productsLearn the principles that guide effective, responsible design for AI. I'll teach you the fundamental principles and approaches behind experiences that blend the power of AI with intuitive, human-centered design. From initial investigation and research to designing features, functionality and evaluation metrics to gauge usability and measure trust, I'll tackle all the core areas you need to know about.Why it matters: AI is about more than automation. It's about delivering useful and valuable user experiences that meet both user needs and business goals.Create ethical, trustworthy AI-driven productsI'll show you how to build AI products that users trust-and that won't perpetuate bias or misinformation. You'll learn the ethical considerations you need to think through and how to design with fairness and transparency in mind.Why it matters: Building trust is crucial in AI. Companies are investing in AI solutions that don't just work but are ethical and inclusive. Your ability to design these systems will set you apart.Understand the basics of designing for key GenAI attributes like generative variability and tradeoffs between precision and recall. Generative variability is the heart of GenAI. I'll walk you through two critical questions we, as UXers and designers, have to answer: (1) how do we present multiple, varied outputs to users and (2) how do we guide them in selecting the best one?As a UX or product designer, one of the key decisions you'll face when working with AI systems is how to balance precision and recall. I'll dig intot both concepts and walk you through how to design that balance appropriately.Why it matters: Generative variability is the heart of GenAI, and designing for it requires an approach that's very different from the products we typically tackle. In particular, precision and recall define how accurate and thorough your AI's results will be - and getting the balance right directly impacts UX and user trust.Turn AI into a business asset for your clients or employers Design AI systems that do more than just function-they deliver real business value. I'll teach you how to align AI-driven products with business objectives, ensuring that the user experience drives results.Why it matters: Your ability to create AI-enabled products that solve real business challenges will make you a valuable asset to your employer.Be a leader in AI-enabled UX and product designAs AI continues to reshape the design industry, you'll be equipped to lead AI-focused design projects, taking your career to the next level. No more waiting on engineers to explain AI to you. You'll be the one leading the collaborative charge to determine how AI best fits into product design.Why it matters: Leaders in this field don't wait for opportunities-they create them. Position yourself as a forward-thinking designer who is driving AI adoption and innovation.Who this course is for:New UX and Product Designers: If you're starting out and want to make your career trajectory more stable and secure, this course will give you the foundation to be an asset to your employer from day one.Experienced UXers, Product Designers and Product Developers: If you're already working in the industry and want to stay competitive and lead the next wave of innovation, this course will teach you how to begin integrating AI product design into your current design skill set - and to have informed, productive conversations with software engineers and data scientists on GenAI projects.I've included a massive GenAI UX workbook you can use on real-world projects.You can download and use this 164-page companion workbook to use both as practice and to help you through the process of designing for GenAI in your daily work as well. Use the guidance and 89 exercises across 22 mission-critical topics in GenAI design for any real-world GenAI projects that come your way - the exercises here are designed to help you through the process, from concept to execution. Who this course is for New UX and Product Designers: If you're starting out and want to make your career trajectory more stable and secure, this course will give you the foundation to be an asset to your employer from day one. Experienced UXers, Product Designers and Product Developers: If you're already working in the industry and want to stay competitive and lead the next wave of innovation, this course will teach you how to begin integrating AI product design into your current design skill set - and to have informed, productive conversations with software engineers and data scientists on GenAI projects. UX Researchers, UX Writers, Product Managers and anyone wondering what they need to know in order to play a role in designing GenAI-driven products. Homepage https://www.udemy.com/course/genai-fundamentals-for-ux-designers-researchers/ Screenshot Rapidgator https://rg.to/file/063cd88a4490f38ee0fc2c2e51fd751a/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part3.rar.html https://rg.to/file/8eebc02346b71b36e472720518547e10/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part4.rar.html https://rg.to/file/b94257c35be7534e875c506b524d828e/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part1.rar.html https://rg.to/file/bca9c8f730c5393d9ed726011ba33d50/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part2.rar.html Fikper Free Download https://fikper.com/eCPZXwg0GA/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part2.rar.html https://fikper.com/obbYagVllB/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part1.rar.html https://fikper.com/rLh6ucfqjw/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part4.rar.html https://fikper.com/zYC1iCO4rH/dglok.GenAI.Fundamentals.for.UX.Designers..Researchers.part3.rar.html No Password - Links are Interchangeable

Free Download GenAI - Langchain for javascript developers Published 10/2024 Created by Amit Gupta MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 38 Lectures ( 3h 13m ) | Size: 1.62 GB Learn Generative AI and Langchain by building real life use cases in javascript/typescript What you'll learn Generative AI technology and building LLM powered applications Langchain with Javascript/Typescript using latest Langchain version Build RAG application using private data Build chatbot application using LLMs Working with different LLMs and LLM providers Langchain: LCEL, chains, retrievers, splitters, output parsers, chat memory, langsmith Solid understand of concepts: embeddings, vector databases, LLM parameters Requirements Basic JavaScript/Typescript knowledge, experience with Nodejs Basic software engineering concepts No machine learning experience is needed Description Welcome to the Generative AI Course for JavaScript Developers! This course is tailored specifically for JavaScript professionals ready to advance their careers in the rapidly growing field of generative AI. While AI and machine learning have traditionally been dominated by Python, generative AI has opened up new possibilities, allowing JavaScript developers to build high-quality, LLM powered applications.Who Should Take This Course? This course is designed for developers and architects with JavaScript and Node.js experience who are eager to build applications powered by large language models (LLMs). You'll learn how to use JavaScript with LangChain to create generative AI applications, mastering core concepts like RAG (retrieval-augmented generation), embeddings, vector databases, and more. By the end, you'll be equipped to develop robust generative AI applications.Course Journey: We start with setting up the development environment, creating basic applications to explore key frameworks. Then, we'll dive into advanced topics, building real-world applications with features like retrievable augmented generation and adding conversational layers with chat history.Key Topics Covered:LangChain with JavaScript/TypeScriptLLMs: Working with top providers like AWS Bedrock, OpenAI, and AnthropicPrompts & PromptTemplatesOutput ParsersChains: Including legacy chains and LCELLLM Parameters: Temp, Top-p, Top-kLangSmithEmbeddings & VectorStores (e.g., Pinecone)RAG (Retrieval Augmentation Generation)Tools: Web crawlers, document loaders, text splittersMemory & Chat HistoryThroughout the course, you'll engage in hands-on exercises and build real-world projects to reinforce each concept, ensuring a solid foundation in generative AI with JavaScript. By course completion, you'll be proficient in using LangChain to develop versatile, high-performance LLM applications.What's Included? This course is also a community experience. With lifetime access, you'll receive:GitHub repositories with complete course codeAccess to an exclusive Discord community for support and discussion on GenAI topicsFree updates and continuous improvements at no extra costDisclaimers:This is not a beginner course; software engineering experience and proficiency in JavaScript are assumed.We will be using the VSCode IDE (though any editor is welcome).Some LLM services may require payment, but we'll utilize free options whenever possible. Who this course is for Javascript developers and architects looking to advance their career with Generative AI technology Engineers that want to learn how to build Generative AI based applications with LangChain Homepage https://www.udemy.com/course/genai-langchain-for-javascript-developers/ Screenshot Rapidgator https://rg.to/file/1449164a6b104ebe0fd469ac8e66a622/blkrx.GenAI..Langchain.for.javascript.developers.part2.rar.html https://rg.to/file/c7b0bae4d7ad6b8599ad827467d9a0c8/blkrx.GenAI..Langchain.for.javascript.developers.part1.rar.html Fikper Free Download https://fikper.com/Xp6QDibeze/blkrx.GenAI..Langchain.for.javascript.developers.part2.rar.html https://fikper.com/sR5fMJ3nB3/blkrx.GenAI..Langchain.for.javascript.developers.part1.rar.html No Password - Links are Interchangeable

Free Download Cybersecurity Defense with GenAI Last updated 10/2024 Created by Dr. Amar Massoud MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 13 Lectures ( 1h 42m ) | Size: 607 MB Mastering Cybersecurity with GenAI: Automate Threat Detection, Response, and Security Operations What you'll learn Understand how to integrate GenAI into cybersecurity frameworks. Automate routine security tasks using Generative AI. Improve threat detection and response with GenAI. Enhance security posture through AI-driven vulnerability management. Requirements Basic understanding of cybersecurity concepts and practices is helpful but not required. Description Discover how Generative AI (GenAI) is revolutionizing cybersecurity in this comprehensive course. Designed for cybersecurity professionals, IT managers, and anyone interested in AI's role in security, this course will teach you how to leverage GenAI to automate and enhance your security operations.You'll learn how to integrate GenAI into existing security frameworks, improving threat detection and response times while automating routine security processes. By the end of the course, you'll understand how to optimize your security posture through AI-driven vulnerability management and real-time threat analysis. You'll also explore best practices for automating tasks like patch management, access control, and incident reporting to reduce manual workloads and minimize the risk of human error.With hands-on labs and practical examples, you'll gain the skills needed to implement GenAI in real-world security environments. Whether you're managing a small team or an enterprise-level operation, this course will equip you with the knowledge to enhance your organization's cybersecurity strategy.Key topics include GenAI for threat hunting, automating security reports, and managing security operations ticketing systems. This course is perfect for security analysts, IT leaders, and tech enthusiasts looking to stay ahead in the rapidly evolving field of cybersecurity.Enroll now to unlock the power of AI and take your cybersecurity operations to the next level with GenAI! Who this course is for Cybersecurity professionals looking to leverage AI for enhanced security operations. IT managers aiming to integrate GenAI into their security infrastructure. Security analysts interested in automating and optimizing security tasks. Anyone curious about how AI can transform cybersecurity practices. Homepage https://www.udemy.com/course/cybersecurity-defense-with-genai/ Screenshot Rapidgator https://rg.to/file/7de27cc0723cca962effc0cd3946eee9/nrxnr.rar.html Fikper Free Download https://fikper.com/q5Ub52fJ2H/nrxnr.rar.html No Password - Links are Interchangeable

Free Download Cybersecurity Defense with GenAI - Foundations & Fundamentals Last updated 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 36m | Size: 600 MB Learn how generative AI transforming cybersecurity defense with insights into AI-driven threat detection and response!! What you'll learn Introduction to Cybersecurity and AI Generative AI Fundamentals AI-Driven Threat Detection Automating Incident Response with AI Predictive Analytics in Cybersecurity AI-Based Vulnerability Management Ethical Considerations in AI-Driven Cybersecurity Case Studies: AI in Cyber Defense Future of AI in Cybersecurity Best Practices for Implementing AI in Cybersecurity Requirements There are no specific technical prerequisites, but a basic understanding of cybersecurity principles, IT infrastructure, and general AI concepts is helpful. Prior experience in IT security or cybersecurity roles will enhance the learning experience, though it's not mandatory for those with an interest in this field. Description Cybersecurity Defense with GenAI Fundamentals is a course that explores the intersection of artificial intelligence (AI) and cybersecurity. It introduces how generative AI (GenAI) can be used to bolster defense mechanisms against cyber threats, automate threat detection, and improve incident response strategies. The course covers the theoretical foundations of using AI in cybersecurity while providing insights into the evolving role of AI in protecting digital infrastructures.As cyber threats become increasingly sophisticated, traditional methods of defense are often insufficient. Generative AI has the potential to revolutionize cybersecurity by automating the detection of anomalies, predicting attack patterns, and responding to incidents in real-time. Understanding how to leverage AI for cybersecurity defense can significantly improve the resilience of organizations to attacks, making this knowledge crucial for IT and security professionals.Advantages of Learning Cybersecurity Defense with GenAI Fundamentals1. Enhanced Cyber Defense: Learn how AI can be used to proactively detect and mitigate threats.2. Automation of Cybersecurity Processes: Understand how AI automates routine tasks like threat detection, vulnerability scanning, and response automation.3. Predictive Analytics: Gain insights into how AI predicts future attacks and enhances defense strategies.4. Improved Incident Response: Discover how AI reduces the time and resources needed to respond to security incidents.5. Future-Proof Skills: Stay ahead of the curve by mastering cutting-edge technologies shaping the future of cybersecurity.This course focuses on theoretical concepts and foundations, and there will be no labs, technical configuration, or setup required. Who this course is for This course is ideal for cybersecurity professionals, IT security teams, and anyone in IT leadership roles who want to leverage generative AI to strengthen their organization's cybersecurity defenses. It is also suitable for AI enthusiasts looking to apply their knowledge to cybersecurity challenges. By learning the fundamentals of GenAI in cybersecurity, professionals can improve their threat mitigation skills and stay prepared for the future of cyber defense. Homepage https://www.udemy.com/course/cybersecurity-defense-with-genai-foundations-fundamentals/ Screenshot Rapidgator https://rg.to/file/e8bd99827a6d5c78b7a2da93bb8c4d2c/dilmf.Cybersecurity.Defense.with.GenAI.Foundations..Fundamentals.rar.html Fikper Free Download https://fikper.com/U7YZUWrPBl/dilmf.Cybersecurity.Defense.with.GenAI.Foundations..Fundamentals.rar.html No Password - Links are Interchangeable

Free Download Amazon Bedrock Unleash Genai Without Code 100% Drag & Drop Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 3.03 GB | Duration: 5h 57m Bedrock Studio, PartyRock, Prompt Flows, Agents - using different models like Claude Sonnet, Llama, Titan, Stability AI. What you'll learn Master the fundamentals of generative AI and its business applications Navigate the Amazon Bedrock console with confidence Generate high-quality written content using AI models Create custom images with AI using simple text prompts Build interactive chatbots and AI assistants without coding Customize AI outputs to match your brand voice and style Implement responsible AI practices and ethical considerations Integrate AI solutions into existing business workflows Evaluate and optimize AI performance for better results Complete hands-on, real-world AI projects using Amazon Bedrock Requirements Basic computer skills and familiarity with web browsers Access to a computer with a stable internet connection An AWS account No prior coding or programming experience required Basic understanding of cloud computing concepts (helpful but not mandatory) Familiarity with common business software and applications Enthusiasm to learn about AI and its practical applications Willingness to experiment with new technologies A business, creative, or personal project idea to apply AI concepts (optional) Description Course OverviewUnlock the potential of generative AI with Amazon Bedrock - no coding required! This course is designed for professionals, creatives, and enthusiasts who want to harness the power of advanced AI models without delving into complex programming. Learn to use Amazon Bedrock's user-friendly interface to create, customize, and deploy AI-powered solutions for various business and creative needs.What You'll LearnUnderstand the basics of generative AI and its applicationsNavigate the Amazon Bedrock console with easeUse pre-built AI models for text generation, summarization, and translationCreate stunning images with AI using simple promptsDevelop chatbots and conversational AI without codingCustomize AI outputs to suit your specific needsImplement best practices for responsible AI useIntegrate Bedrock-powered solutions into your workflowCourse ContentIntroduction to Generative AI and Amazon BedrockGetting Started with the Amazon Bedrock ConsoleExploring Available Foundation ModelsText Magic: Generation, Summarization, and TranslationVisual Creativity: AI Image Generation Made EasyBuilding Your Own AI AssistantCustomizing AI Outputs for Your BrandResponsible AI: Ethics and Best PracticesIntegrating Bedrock into Your Business WorkflowReal-world Use Cases and Practical ProjectsPrerequisitesBasic computer skillsNo coding experience requiredFamiliarity with AWS is helpful but not necessaryWho This Course is ForBusiness professionals seeking to implement AI solutionsContent creators looking to enhance their work with AIEntrepreneurs exploring AI-powered business ideasEducators interested in bringing AI into the classroomAnyone curious about using advanced AI without codingEmbark on your no-code AI journey with Amazon Bedrock and revolutionize the way you work, create, and innovate! Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Content Lecture 3 Connect With Me!! Section 2: Playground - Explore & Relate Lecture 4 Introduction to Bedrock Lecture 5 PartyRock - Experience Bedrock like ChatGPT Lecture 6 Understanding UI Lecture 7 Enabling Model Access Lecture 8 Post Model Access Lecture 9 Using Chat Playground Lecture 10 Modifying Response with Prompts Lecture 11 Using Text Playground Lecture 12 Using Image Playground Section 3: Foundation Concepts Lecture 13 What is AI Lecture 14 What is Generative AI Lecture 15 Opportunities available in GenAI Lecture 16 AI, GenAI, ML, Deep Learning Relation Lecture 17 FM vs LLM Lecture 18 Retrieval Augmented Generation Lecture 19 Crawling and Indexing Lecture 20 Understanding Prompt Engineering Lecture 21 Types of Prompt Engineering Lecture 22 Bedrock Pricing Section 4: Configurations - Inference Parameters Lecture 23 Understanding Inference Parameters Lecture 24 Temperature Hands-On Lecture 25 Temperature Hands-On (II) Lecture 26 Top P Hands-On Lecture 27 Top P Hands-On (II) Lecture 28 Are Models Configurations always right? Lecture 29 Increase chances to get required results Lecture 30 Top K Hands-On Lecture 31 Most Probable Solution Hands-On Lecture 32 Additional Configurations Lecture 33 System Prompts Lecture 34 Maximum Length Lecture 35 Stop Sequence Section 5: Safeguards Lecture 36 Understandig Safeguards Lecture 37 Guardrails SetUp Lecture 38 Using Guardrails Lecture 39 Watermark Detection Section 6: Builder Tools Lecture 40 Understanding Builder Tools Lecture 41 Prompt Management Lecture 42 Knowledge Base - Using Root User Lecture 43 IAM Users & Roles Lecture 44 IAM Policy Lecture 45 Knowledge Base - Using IAM User Lecture 46 Understanding Agents Lecture 47 Agents Walkthrough Lecture 48 Creating Agents using Assistant Lecture 49 Defining Agents Manually Lecture 50 Adding Action Groups & Guardrails in Agents Lecture 51 Understanding Prompt Flow Lecture 52 Prompt Flow with KB Lecture 53 PromptFlow with Prompt Management Lecture 54 PromptFlow with Prompt Creation & KB Lecture 55 PromptFlow with Condition Lecture 56 PromptFlow to check eligibility to vote Section 7: Bedrock Studio SetUp Lecture 57 Understanding Bedrock Studio Lecture 58 IAM Organisation Lecture 59 IAM Identity Center Lecture 60 Adding User in Identity Center Lecture 61 Enabling User in Identity Center Lecture 62 Roles & Permissions required for Studio Lecture 63 Studio Workspace Creation Lecture 64 Assign Users to Workspace Section 8: Bedrock Studio - Chat App Lecture 65 Bedrock Studio Workspace UI Lecture 66 Initial Chat App Lecture 67 Guardrails with Chat App Lecture 68 Editing Guardrails in Chat App Lecture 69 Using Knowledge Base in Chat App Lecture 70 Solution of Size Error in Chat App Section 9: Bedrock Studio - Prompt Flow App Lecture 71 Project Isolation Lecture 72 Basic Prompt Flow App Lecture 73 Flow App with KB & prompts Lecture 74 Prompt Flow with Conditions Section 10: Choosing the right FM Lecture 75 Why right FM is necessity? Lecture 76 Criteria for choosing right FM Lecture 77 Model Evaluation Lecture 78 Different Models Functionality Business professionals seeking to implement AI solutions without coding,Entrepreneurs and small business owners looking to leverage AI capabilities,Marketing and content creators wanting to enhance their work with AI tools,Product managers interested in integrating AI features into their offerings,Customer service managers aiming to implement AI-powered chatbots,HR professionals looking to streamline processes with AI assistance,Educators and trainers curious about incorporating AI in their teaching methods,Consultants and advisors wanting to understand AI for client recommendations,Digital transformation specialists guiding AI adoption in organizations,Non-technical innovators with ideas for AI applications,Professionals in any field interested in staying current with AI trends,Anyone curious about AI who wants a hands-on, no-code learning experience Screenshot Homepage https://www.udemy.com/course/amazon-bedrock-unleash-genai-without-code-100-drag-drop/ Rapidgator https://rg.to/file/03515d0dfc4c33e4d60ef2ede99d5bb6/ukfpw.Amazon.Bedrock.Unleash.Genai.Without.Code.100.Drag..Drop.part1.rar.html https://rg.to/file/42c69f51fa30608d71cc633fda0715c2/ukfpw.Amazon.Bedrock.Unleash.Genai.Without.Code.100.Drag..Drop.part2.rar.html Fikper Free Download https://fikper.com/cG9ZA317JK/ukfpw.Amazon.Bedrock.Unleash.Genai.Without.Code.100.Drag..Drop.part1.rar.html https://fikper.com/vZS4FlGyr5/ukfpw.Amazon.Bedrock.Unleash.Genai.Without.Code.100.Drag..Drop.part2.rar.html No Password - Links are Interchangeable

Free Download 30 Days Of Genai Mastery Elevate Your Work & Life With Ai T Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.72 GB | Duration: 2h 39m ChatGPT, Midjourney, DALL-E, Leonardo, HeyGen, Suno, Microsoft Copilot, Gemini, Runway and more! What you'll learn How to use ChatGPT, Microsoft Copilot and Gemini for content generation How to generate images with Midjourney, DALL-E, OpenArt, etc Video generation with Pika, Runway AI avatar creation with HeyGen, Elai, HourOne and more Song generation with Suno And much more! Requirements There are no special requirements for taking this course except your desire to enhance your work/daily routine with powerful GenAI tools. Description "I never imagined GenAI could make such a difference in my work! Each tool introduced in this course is easy to understand, and the practical examples have saved me hours of effort!"- Paul, Marketing Specialist30 Days of GenAI Mastery: Elevate Your Work & Life with AI Tools is designed specifically for you! We know how valuable your time is, so:- Daily lessons that take just a few minutes to complete- Short, actionable videos that help you master Generative AI tools effortlessly- Lifetime access to content, with continuous updates as GenAI evolves- Expert support on the most impactful tools in the AI space todayEnroll now and gain access to tools that will save you time and help you unlock new levels of creativity and productivity!What You'll Learn in This Course:- Create engaging content using AI-powered tools for text, images, video, and more- Automate tedious tasks to boost your productivity- Use top GenAI tools like Gemini, ChatGPT, DALL-E, Midjourney, Leonardo, and more- Explore advanced techniques to generate creative ideas for your work and projects- Use Generative AI to enhance your social media, marketing, design, and everyday tasksWhat's Included:- 30 daily lessons introducing you to the most cutting-edge AI tools- Hands-on tutorials and real-life examples to solidify your understanding- Step-by-step guides on using GenAI for everything from creating content to streamlining workflowsThis Course is Perfect for:- Creatives, entrepreneurs, and professionals looking to stay ahead of the curve- Business owners eager to boost efficiency and productivity- Digital marketers and social media managers who want to create engaging content faster- Anyone curious about the power of Generative AI and how it can transform their lifeGet Started Now and start seeing the transformative effects of AI in your work and life. Don't miss the opportunity to master these game-changing tools and elevate your potential!Join today and unlock the future of GenAI-driven productivity and creativity!Do you need to be concerned?This course comes with a 30-day money-back guarantee.See you in the first lecture! Overview Section 1: Introduction to the Course Lecture 1 Introduction Lecture 2 How to Study on Udemy Section 2: First Week of GenAI Lecture 3 Introduction to ChatGPT Lecture 4 ChatGPT Life Hacks Lecture 5 A step-by-step guide to creating your own GPT's Lecture 6 ChatGPT for Self-education & Personal Growth Lecture 7 Introduction to Microsoft Copilot Lecture 8 Use of Google Gemini and Google Workspace Lecture 9 Visual Content with DALL-E Section 3: Second Week of GenAI Lecture 10 Getting Started with Midjourney Lecture 11 Midjourney's interface, features, and settings Lecture 12 Other Midjourney features Lecture 13 Generating images with OpenArt Lecture 14 AI Powered Social Media Content with Stockimg Lecture 15 Portrait Generation with Picsi Lecture 16 Techniques for video content creation Section 4: Third Week of GenAI Lecture 17 Video Creation with Pika Lecture 18 Video Creation with Runway Lecture 19 Your First Avatar with HeyGen Lecture 20 Elai for Avatars generation Lecture 21 AI Avatar Creation with HourOne AI Lecture 22 Audio Content Creation with Suno Lecture 23 Introduction to Leonardo Section 5: Fourth Week of GenAI Lecture 24 Using PhotoRoom and Flair for product photography Lecture 25 Convert Audio and Video into Text with Cockatoo Lecture 26 Streamling Content Creation with Simplified AI Lecture 27 Gamma.app for presentation generation Lecture 28 Upgrade Your Ads Creation with AdCreative.ai Lecture 29 AI Image Editing with Remove.bg Section 6: Final section Lecture 30 Summary Lecture 31 How to leave a review Lecture 32 How to get a certificate Anyone who knows how to use AI but wants to enhance their knowledge.,Everybody who is curious about learning new GenAI tools and how to integrate them into daily tasks.,Digital marketers, content creators, social media marketers, and other professionals who want to leverage AI to elevate their work. Screenshot Homepage https://www.udemy.com/course/30-days-of-genai-mastery-elevate-your-work-life-with-ai/ Rapidgator https://rg.to/file/bc60576842994a39868291f1e91ffc8a/ujfff.30.Days.Of.Genai.Mastery.Elevate.Your.Work..Life.With.Ai.T.part1.rar.html https://rg.to/file/e0626292febef2371c6ae2215e92326a/ujfff.30.Days.Of.Genai.Mastery.Elevate.Your.Work..Life.With.Ai.T.part2.rar.html Fikper Free Download https://fikper.com/JiThA3BBFU/ujfff.30.Days.Of.Genai.Mastery.Elevate.Your.Work..Life.With.Ai.T.part1.rar.html https://fikper.com/csNd5lYwyX/ujfff.30.Days.Of.Genai.Mastery.Elevate.Your.Work..Life.With.Ai.T.part2.rar.html No Password - Links are Interchangeable

Free Download GenAI World - LLM, Fine-tuning, RAG & Prompt engineering Published 10/2024 Created by Rabbitt Learning MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 12 Lectures ( 42m ) | Size: 561 MB The single source of truth What you'll learn: Understand the fundamentals of prompting in the context of large language models (LLMs). Learn the importance of prompt engineering for optimizing model perform Explore advanced concepts like Direct Preference Optimization (DPO) and Parameter-Efficient Fine-Tuning (PEFT). Gain insights into Retrieval Augmented Generation (RAG), understanding its components and how it enhances LLM capabilities. Requirements: Yes, students should have: A foundational understanding of artificial intelligence and machine learning concepts, especially related to language models. Proficiency in Python programming, as the course includes detailed code examples and exercises. Familiarity with deep learning frameworks. Basic knowledge of natural language processing (NLP) and transformer models. Access to necessary computational resources, such as a GPU-enabled environment. Description: This course covers everything from Large Language Models (LLMs), prompt engineering to parameter-efficient fine-tuning (PEFT) and advanced concepts like Direct Preference Optimization (DPO). You'll also dive deep into Retrieval Augmented Generation (RAG) to enhance your LLMs' capabilities by integrating retrieval systems for superior responses.By the end of this course, you'll be equipped to create AI solutions that align perfectly with human intent and outperform standard models. What You'll Learn:Craft powerful and effective prompts for LLMs to optimize outputs.Master Direct Preference Optimization (DPO) and PEFT for domain-specific fine-tuning.Implement Retrieval Augmented Generation (RAG) to elevate model performance.Gain insights into state-of-the-art LLM capabilities, focusing on practical and advanced techniques.Develop customized solutions with hands-on code examples and exercises. What you will Get A foundational understanding of artificial intelligence and machine learning concepts, especially related to language models. Proficiency in Python programming, as the course includes detailed code examples and exercises. Familiarity with deep learning frameworks. Basic knowledge of natural language processing (NLP) and transformer models. Access to necessary computational resources, such as a GPU-enabled environment. In addition to the core topics, our course also features real-world case studies on fine-tuning, prompt engineering, and Retrieval Augmented Generation (RAG). These case studies offer practical, hands-on insights into how these techniques are applied in real AI projects .These case studies provide a practical framework for applying the theoretical concepts covered in the course, helping learners implement these methods in their own projects. Who this course is for: This course is ideal for: Machine learning engineers and data scientists looking to enhance their skills in fine-tuning large language models. AI researchers and practitioners interested in advanced techniques like RAG, PEFT, and QLoRA. Developers and programmers aiming to implement AI solutions that require domain-specific model customization. Students and academics studying artificial intelligence, machine learning, or natural language processing. Anyone interested in state-of-the-art AI technologies and how to apply them effectively in real-world scenarios. Homepage https://www.udemy.com/course/genai-world-llm-fine-tuning-rag-prompt-engineering/ Rapidgator https://rg.to/file/f59fdf8623032aa4f829304a12fe9127/nonlu.GenAI.World..LLM.Finetuning.RAG..Prompt.engineering.rar.html Fikper Free Download https://fikper.com/Tb2IRzSxjq/nonlu.GenAI.World..LLM.Finetuning.RAG..Prompt.engineering.rar.html No Password - Links are Interchangeable

Free Download GenAI Cybersecurity and Ethical Hacking - Zero to Hero Pro Published 9/2024 Created by Paul Carlo Tordecilla MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 111 Lectures ( 7h 30m ) | Size: 4.11 GB Transform into a Cybersecurity Expert with Hands-On Training in Ethical Hacking, AI, and Machine Learning What you'll learn: Students enrolled in this course will gain a comprehensive understanding of cybersecurity and IT security fundamentals. They will learn strategies to protect against hackers and prevent hacking attempts. They will delve into IT security and information security (INFOSEC). Students will develop robust cybersecurity defense strategies. The course covers networking basics and their crucial role in cybersecurity. Learners will explore ethical hacking techniques, starting from a beginner's perspective. They will progress to mastery of Kali Linux command line essentials. They will learn how to conduct information gathering, reconnaissance, and vulnerability analysis. Students will explore exploit techniques and engage in hands-on exploitation using the Metasploit Framework. Advanced security measures such as password attacks, wireless security, and web application security are integral parts of the curriculum. Students will learn automated web vulnerability scanning and social engineering. The course delves into the integration of artificial intelligence into cybersecurity strategies. It covers topics like cybersecurity with Generative AI and OpenAI. Students will utilize Python for cybersecurity applications. They will master threat detection and response with GenAI. Practical experience with tools like Splunk is provided. Techniques for anonymous browsing and privacy protection are taught. Through hands-on projects, students will develop an AI hacking tool. They will perform packet analysis and encryption. Students will build an AI-powered Windows Event Log Analyzer with OpenAI integration and machine learning. Requirements: To take this course, students should have basic computer knowledge. They should be familiar with using a computer and navigating operating systems. An understanding of basic networking concepts is helpful but not mandatory. A computer running Windows, macOS, or Linux with internet access is required. Students should be able to install software such as Kali Linux, Python, and other tools discussed in the course. No prior experience in cybersecurity or programming is necessary. A willingness to engage in hands-on projects and practical exercises is essential. Students should have an open mind and a keen interest in learning about both defensive and ethical hacking techniques. Description: Are you prepared for that transformative journey into the world of cybersecurity and ethical hacking? "GenAI Cybersecurity and Ethical Hacking: Zero to Hero Pro " is a comprehensive learning course, with state-of-the-art tools that will surely wake up your cybersecurity master ship skills in today's rapidly evolving digital landscape.We start from square one and take you through the absolute basics of networking, IT security, and INFOSEC. We understand how to counter hackers and prevent hacking attempts with our discussion on cybersecurity defense strategies. As we continue, we will then dive into actual hacking techniques into information gathering, reconnaissance, vulnerability analysis, and various forms of exploitation using tools like Kali Linux and the Metasploit Framework.It deals with leading-edge technologies, focusing on artificial intelligence and machine learning in revolutionizing cybersecurity. In this program, you have the opportunity to go deep into topics such as Cybersecurity with Generative AI and OpenAI and learn how to implement threat detection and response capabilities using GenAI. You would be working on real-world projects; these include developing an AI hacking tool, packet analysis, and encryption, along with building an AI-powered Windows Event Log Analyzer by integrating OpenAI.Instead, the course will focus more on the development of students' skills in anonymous browsing, protection of privacy, password attack, wireless security, web application security, and also social engineering. Learn Splunk in the best way with hands-on experience: Automate web vulnerability scanning and stay ahead of the curve of potential threats.By the end of this course, you will be equipped with a full-scale skill set that covers the traditional cybersecurity approach along with innovative AI-driven approaches. This would be the opening to become a guardian of the digital world for those who are either entering a career or are upgrading their knowledge.Enroll now and step closer to GenAI Cybersecurity and Ethical Hacking: Zero to Hero Pro! Who this course is for: This course is ideal for beginners and aspiring professionals who are new to cybersecurity and ethical hacking and wish to start a career in this dynamic field. It is suitable for students and enthusiasts eager to learn about both the fundamentals and advanced topics in cybersecurity. IT professionals, including network administrators and system administrators looking to enhance their cybersecurity skills, will find this course valuable. Security professionals seeking to update their knowledge with the latest AI-powered tools and techniques are encouraged to enroll. The course is beneficial for ethical hackers and security enthusiasts aiming to expand their toolkit with AI and machine learning applications. It is also for anyone interested in understanding the operation of cyber threats and how to defend against them. Additionally, AI and machine learning enthusiasts curious about the intersection of these technologies with cybersecurity will greatly benefit from this course. Professionals looking to apply AI and machine learning concepts to real-world security challenges will also find this course valuable. Homepage https://www.udemy.com/course/genai-cybersecurity-and-ethical-hacking-zero-to-hero-pro/ TakeFile https://takefile.link/21qx46bznxtq/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part1.rar.html https://takefile.link/73sxfeci5sdq/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part2.rar.html https://takefile.link/x814fvvo32s8/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part3.rar.html https://takefile.link/pux6h0sk32nk/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part4.rar.html https://takefile.link/a75ni7yti8xb/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part5.rar.html Rapidgator https://rg.to/file/fc59390c3c63445f7ca3a999f88beb1d/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part1.rar.html https://rg.to/file/d92ebe1e67c402dd6423ce1f5ad64d16/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part2.rar.html https://rg.to/file/5ec54e51c03cc359dcb729d0c28b658b/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part3.rar.html https://rg.to/file/9039ef61919ef4fad7359f957e099e75/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part4.rar.html https://rg.to/file/34464afcc2c3fcbbefbe0fe3e47fc133/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part5.rar.html Fikper Free Download https://fikper.com/3yAQtSoatf/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part1.rar.html https://fikper.com/lLRng5ItHg/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part2.rar.html https://fikper.com/hjklSJZJ2e/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part3.rar.html https://fikper.com/UhZMe06u4W/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part4.rar.html https://fikper.com/BRzy5X2aSk/rcnqd.GenAI.Cybersecurity.and.Ethical.Hacking.Zero.to.Hero.Pro.part5.rar.html No Password - Links are Interchangeable

Free Download Mastering Genai - Fine-Tune & Adapt Llms Effectively Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1006.46 MB | Duration: 1h 7m Harness Advanced Techniques in AI: From Fine-Tuning to Ethical Deployment and Optimization What you'll learn Understand and describe the architecture of Generative AI models like GPT and BERT. Apply fine-tuning methods to adapt LLMs to specific tasks and industries. Evaluate and optimize LLM performance through advanced techniques Implement ethical guidelines and best practices in the deployment of GenAI models Requirements Basic understanding of AI concepts and terminology; no advanced technical skills required. Familiarity with Python programming to follow along with coding demos and exercises. Description Explore the cutting-edge field of Generative AI with our course, 'Mastering GenAI: Fine-Tune & Adapt LLMs Effectively.' Designed for professionals and enthusiasts alike, this course offers a deep dive into the mechanisms of large language models such as GPT and BERT. You'll learn how to fine-tune these models to meet specific requirements, ensuring they perform optimally across various industries.Through a mix of theoretical insights and practical exercises, parti[beeep]nts will explore different fine-tuning techniques including supervised, unsupervised, and reinforcement learning methods. The course will also address the critical aspects of model optimization, such as hyperparameter tuning and avoiding overfitting, to enhance both efficiency and accuracy.A significant focus will be on the ethical deployment of these technologies. You'll learn to navigate the complexities of AI ethics, ensuring your AI solutions are fair and equitable. This course will prepare you to effectively adapt and deploy AI models, making you a valuable asset in any tech-driven industry.By the end of this course, parti[beeep]nts will not only understand the theoretical underpinnings of generative AI but also be proficient in implementing and optimizing these models in a practical, ethical, and efficient manner. Whether you're looking to innovate within your organization, kickstart a career in AI, or academically explore AI technologies, this course will serve as a vital stepping stone to achieving those goals. Overview Section 1: Introduction Lecture 1 What is Gen AI ? Lecture 2 What are LLMs ? Section 2: Real-world Large Language Models Lecture 3 Decision Making: Build, Purchase, or Enhance Lecture 4 Introduction to Zero-shot Classification Lecture 5 Demonstrating a Proof of Concept Lecture 6 Essentials of Training and Fine-tuning Section 3: Fine-tuning Techniques for LLMs Lecture 7 Training and Fine-tuning Lecture 8 Supervised Fine-tuning vs. Parameter Efficient Fine-tunin Lecture 9 Approaches to Fine-tuning Lecture 10 Reinforcement learning from human feedback This course is ideal for AI enthusiasts, data scientists, and developers interested in extending their expertise into the realm of fine-tuning and adapting large language models,Suitable for IT professionals looking to leverage GenAI for improving business processes and creating innovative solutions.,Perfect for academic researchers and students in computer science who want practical experience with state-of-the-art AI technologies.,Security architects and engineers who aim to understand the cybersecurity implications of deploying generative AI models in their operations. Homepage https://www.udemy.com/course/fine-tuning-and-adapting-genai-models/ Rapidgator https://rg.to/file/67d204c8d2478aefbe5e4b8e60c55482/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part1.rar.html https://rg.to/file/63884c75c2442f161a951af07e9588ef/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part2.rar.html Fikper Free Download https://fikper.com/8vPTUwz27k/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part1.rar.html https://fikper.com/kXOripHkgH/ezmxr.Mastering.Genai.FineTune..Adapt.Llms.Effectively.part2.rar.html No Password - Links are Interchangeable

Free Download GenAI and Predictive AI Architecture Foundations Released: 09/2024 Duration: 1h 16m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 157 MB Level: Intermediate | Genre: eLearning | Language: English Get a clear understanding of how AI solutions actually work, starting with their basic architectures and advancing to system components and architectural differences between generative AI and predictive AI systems. Join LinkedIn Top Voice and best-selling author Thomas Erl as he breaks down and explains, in plain English, the foundational building blocks and the primary moving parts behind contemporary AI solution environments. This course provides genuine insight into how AI systems function in the real world, and is essential for professionals already working with application and enterprise architectures, as well as professionals in the AI and data science fields. Homepage https://www.linkedin.com/learning/genai-and-predictive-ai-architecture-foundations?u=121350530 TakeFile https://takefile.link/ng378cbfiiuv/wmlwn.GenAI.and.Predictive.AI.Architecture.Foundations.rar.html Rapidgator https://rg.to/file/96dcdb1f7b91625374811c94b2392617/wmlwn.GenAI.and.Predictive.AI.Architecture.Foundations.rar.html No Password - Links are Interchangeable

Free Download [NEW] GitHub Copilot - Use GenAI to Write Terraform For You! Published 9/2024 Created by Bryan Krausen • 130,000+ Enrollments Worldwide MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 26 Lectures ( 3h 44m ) | Size: 1.64 GB Increase Your Productivity! Leverage GenAI to Write and Optimize Your HashiCorp Terraform Code with GitHub Copilot What you'll learn: Use GitHub Copilot for developing Terraform code, leveraging GenAI capabilities effectively. Accelerate your Terraform development cycles by utilizing GitHub Copilot to generate and optimize infrastructure-as-code (IaC) scripts Improve code quality and consistency through automated suggestions and templates provided by GitHub Copilot Learn techniques to troubleshoot and customize GitHub Copilot's suggestions to better align with specific project requirements and best practices in Terraform d Requirements: Familiarity with the basics of Terraform, including understanding resources, providers, variables, and state management. An active GitHub account is necessary to access GitHub Copilot and to practice code examples provided in the course Familiarity with using a text editor or integrated development environment (IDE) of choice (e.g., VS Code) to edit and manage code files Description: Are you ready to supercharge your HashiCorp Terraform coding with the power of AI? Welcome to the course that will revolutionize the way you approach Infrastructure as Code (IaC) in your DevOps workflow.Imagine having an AI-powered coding assistant that understands HashiCorp Terraform as well as you do, helping you quickly write, optimize, and troubleshoot your infrastructure configurations. That's exactly what GitHub Copilot offers, and in this course, you'll learn how to unlock its full potential.Throughout this course, we'll build complex environments using AWS, using only FREE resources so you can learn without incurring any costs. All skills and concepts can easily be used to build any environment you need and you can even provision resources on other public clouds using the same workflows.Throughout the course, we'll learn and master topics such as:Getting you up to speed with GitHub CopilotShowing you how to integrate this game-changing tool into your existing Terraform and DevOps workflowsUnderstanding how Copilot can help you write Terraform code (HCL) faster, with fewer errors, and more confidenceLearning how to navigate the nuances of AI-generated code, ensuring it's not only functional but also secure and efficient for your infrastructure needs.You'll learn how to develop new code, improve existing code, and even prepare your environment to take advantage of GitHub Copilot.But this course isn't just about learning the tool-it's about transforming the way you work. You'll explore real-world scenarios where Copilot can be your secret weapon, turning tedious coding tasks into quick wins. Whether you're managing cloud infrastructure, automating deployments, or simply looking to improve your Terraform skills, this course is designed to give you the edge in the fast-paced world of DevOps.By the end of this course, you won't just be proficient with GitHub Copilot; you'll be a Terraform powerhouse, capable of leveraging AI to streamline your DevOps processes and deliver results faster than ever before.Don't miss out on this opportunity to elevate your Terraform and DevOps skills-enroll today and take your coding to the next level with GitHub Copilot! Who this course is for: Professionals looking to streamline and automate their Terraform workflow using advanced AI tools like GitHub Copilot Developers interested in enhancing their Terraform skills and leveraging AI-driven assistance to write efficient infrastructure code Individuals responsible for designing and managing cloud infrastructure, seeking to adopt AI technologies for faster and more reliable Terraform deployments Homepage https://www.udemy.com/course/githubcopilot/ Rapidgator https://rg.to/file/4049426a807e13c8d87e674b5ba4b601/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part1.rar.html https://rg.to/file/06b494a87e2bf69c1ed3615fd14ea71d/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part2.rar.html Fikper Free Download https://fikper.com/5CKStp0IuW/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part1.rar.html https://fikper.com/EzJcp7OVfd/urfgj.NEW.GitHub.Copilot.Use.GenAI.to.Write.Terraform.For.You.part2.rar.html No Password - Links are Interchangeable

Free Download GenAI Application Architecture - Scalable & Secure AI Design Published 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 2h 40m | Size: 2.51 GB Build scalable, secure, and efficient GenAI applications with AWS, MLOps, monitoring, and cloud-native architecture What you'll learn Design Scalable GenAI Applications: Learn to architect and build scalable GenAI applications using the LGPL architecture, focusing on Layer, Gate, Pipes Implement Resiliency and Error Handling: Understand how to incorporate error handling, monitoring, logging, and disaster recovery to create resilient GenAI Apps Ensure Security and Cost Efficiency: Develop secure and cost-effective GenAI solutions by leveraging AWS security services, containerization Automate and Optimize with MLOps & CI/CD: Learn to implement MLOps, CI/CD, and Explainable AI (XAI) for streamlined deployment and future-proofing GenAI apps Requirements Basic Knowledge of AI and Machine Learning: Understanding of fundamental AI and machine learning concepts. Familiarity with AWS: Experience with AWS services such as Lambda, S3, and DynamoDB is recommended. Programming Skills: Intermediate-level knowledge of Python is essential. Basic Understanding of Software Architecture: Familiarity with software architecture principles such as scalability, load balancing, and error handling. Description Master the essential techniques and best practices for designing and architecting scalable, secure, and cost-effective Generative AI (GenAI) applications. In this course, you'll explore the principles of the LGPL architecture (Layers, Gates, Pipes, and Loops) and how they apply to building GenAI systems using modern cloud services like AWS. We'll cover critical topics such as load balancing, containerization, error handling, monitoring, logging, and disaster recovery. This course is ideal for those looking to understand GenAI architecture, ensuring applications are resilient, secure, and efficient.What You'll Learn:Architect scalable and secure GenAI applications using the LGPL model.Understand core concepts such as containerization, load balancing, and disaster recovery.Learn best practices for monitoring, logging, and error handling in GenAI systems.Explore MLOps, CI/CD, and security strategies for future-proofing AI applications.This course focuses on the architecture and principles behind building robust GenAI systems, providing the knowledge needed to design effective AI solutions.Enroll now to transform your GenAI Application Architecture skills to the next level. Master GenAI Application Architecture - the core best practices and techniques for building secure, efficient, scalable GenAI Applications.Ready to take your skills to the next level? Join me, and let's get started. See you inside the course! Who this course is for AI Developers and Engineers: Those looking to build scalable, secure, and cost-effective GenAI applications. Cloud Architects: Professionals working with AWS who want to implement GenAI architectures using best practices. Machine Learning Enthusiasts: Individuals with a foundational understanding of machine learning and programming who want to expand into GenAI development. Software Engineers: Engineers seeking to integrate AI into cloud-native applications and implement MLOps pipelines Homepage https://www.udemy.com/course/genai-application-architecture/ Rapidgator https://rg.to/file/eb0dab6db8b173a5e31e2c1124e05cb1/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part1.rar.html https://rg.to/file/a15457d993ba63048e481b780ea9f7a6/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part2.rar.html https://rg.to/file/ce1437543d5df735599d92cd55596194/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part3.rar.html Fikper Free Download https://fikper.com/kOled1XDOx/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part1.rar.html https://fikper.com/5kl1QK2FDE/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part2.rar.html https://fikper.com/sW8thybbOP/idmrc.GenAI.Application.Architecture.Scalable..Secure.AI.Design.part3.rar.html No Password - Links are Interchangeable