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Udemy - Agentic AI and LLM - Build AI Agents with ChatGPT, Ollama and RAG

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Udemy - Agentic AI and LLM - Build AI Agents with ChatGPT, Ollama and RAG (Size: 2.5 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Course Introduction
  1. Introduction (Description).html 3.9 KB
  1. Introduction.mp4 17.9 MB
  10 - Llama & Open-Source LLMs Build AI Locally
  11 - Mistral AI Build Real-World AI Applications
  12 - DeepSeek AI Advanced Reasoning & Real-World Applications
  13 - Course Closure
  2 - Tokens, Embeddings & Context Windows How LLMs Understand Data
  2. What is Tokens in Generative AI (Description).html 1.6 KB
  2. What is Tokens in Generative AI.mp4 7.8 MB
  3 - RAG & Vector Databases Build AI with External Knowledge
  4 - Core Principles of Generative AI Context, Grounding & Safety
  10. How GenAI fall under AI and ML (Description).html 1.9 KB
  10. How GenAI fall under AI and ML.mp4 90.5 MB
  11. What is AI Safety (Description).html 1.3 KB
  11. What is AI Safety.mp4 119.6 MB
  5 - Introduction to AI Agents Concepts & Chatbots vs Agents
  12. AI Agents vs Chatbots Key Differences Explained (Description).html 921.6 B
  12. AI Agents vs Chatbots Key Differences Explained.mp4 91.5 MB
  13. Basics of Agentic AI (Description).html 1.6 KB
  13. Basics of Agentic AI.mp4 86.8 MB
  14. What is an AI Agent Concepts, Components & How It Works (Description).html 1.8 KB
  14. What is an AI Agent Concepts, Components & How It Works.mp4 253 MB
  6 - Hosted vs Local AI Models Open-Source vs Proprietary LLMs Explained
  15. Hosted vs Open Source Model in GenAI (Description).html 1.8 KB
  15. Hosted vs Open Source Model in GenAI.mp4 51 MB
  16. Hosted vs Open Source Models- Which Is Cheaper (Description).html 1.8 KB
  16. Hosted vs Open Source Models- Which Is Cheaper.mp4 27.3 MB
  17. How to Choose Hosted or Open Source Model (Description).html 1.9 KB
  17. How to Choose Hosted or Open Source Model.mp4 8.1 MB
  7 - AI Agent Architecture Types, Memory & System Design
  18. Foundations of AI Agents Types (Description).html 1.7 KB
  18. Foundations of AI Agents Types.mp4 127.6 MB
  19. Foundations of AI Agents Memory (Description).html 1.7 KB
  19. Foundations of AI Agents Memory.mp4 120.3 MB
  20. Foundations of AI Agents Architecture (Description).html 1.9 KB
  20. Foundations of AI Agents Architecture.mp4 148.5 MB
  21. Foundations of AI Agents Some Agentic Tool (Description).html 1.6 KB
  21. Foundations of AI Agents Some Agentic Tool.mp4 102.8 MB
  8 - Build AI Agents with Copilot From Basics to Automation
  22. Introduction to Microsoft Copilot AI for Productivity & Automation (Description).html 1.6 KB
  22. Introduction to Microsoft Copilot AI for Productivity & Automation.mp4 56.4 MB
  23. Build Sales and Revenue Analyzer Agent with Copilot (Description).html 1.7 KB
  23. Build Sales and Revenue Analyzer Agent with Copilot.mp4 200.6 MB
  9 - Build a Product Analyzer AI with ChatGPT UI
  24. Create a Product Analyzer Using ChatGPT UI From Input to Insights (Description).html 1.7 KB
  24. Create a Product Analyzer Using ChatGPT UI From Input to Insights.mp4 102.8 MB
  8. Context Engineering Optimizing Inputs for Smarter LLM Outputs (Description).html 2 KB
  8. Context Engineering Optimizing Inputs for Smarter LLM Outputs.mp4 85.9 MB
  9. What is Context Grounding (Description).html 2 KB
  9. What is Context Grounding.mp4 45.3 MB
  6. What is RAG (Description).html 2.1 KB
  6. What is RAG.mp4 22.7 MB
  7. Vector Database Explained (Description).html 2.1 KB
  7. Vector Database Explained.mp4 56.9 MB
  3. What is Embedding in Generative AI (Description).html 1.7 KB
  3. What is Embedding in Generative AI.mp4 4.9 MB
  4. What is Context Window and how all 3 fits together (Description).html 1.1 KB
  4. What is Context Window and how all 3 fits together.mp4 13.2 MB
  5. Prompt Engineering for AI Techniques, Patterns & Best Practices (Description).html 2.1 KB
  5. Prompt Engineering for AI Techniques, Patterns & Best Practices.mp4 130.1 MB
  32. Closure (Description).html 1.8 KB
  32. Closure.mp4 11 MB
  31. Introduction to DeepSeek AI Models, Capabilities & Use Cases (Description).html 1.7 KB
  31. Introduction to DeepSeek AI Models, Capabilities & Use Cases.mp4 30.1 MB
  27. Introduction to Mistral AI Open-Weight Models & Capabilities (Description).html 1.7 KB
  27. Introduction to Mistral AI Open-Weight Models & Capabilities.mp4 74.1 MB
  28. Prompting Mistral AI with Python Build Smart AI Workflows with Python (Description).html 1.7 KB
  28. Prompting Mistral AI with Python Build Smart AI Workflows with Python.mp4 148.6 MB
  29. Text Classification with Mistral AI Build NLP Models with Python (Description).html 1.7 KB
  29. Text Classification with Mistral AI Build NLP Models with Python.mp4 14 MB
  30. Semantic Analysis with Mistral AI Understanding Text Meaning with Python (Description).html 1.7 KB
  30. Semantic Analysis with Mistral AI Understanding Text Meaning with Python.mp4 83.7 MB
  25. Introduction to Llama Meta’s Open-Source LLM Explained (Description).html 1.7 KB
  25. Introduction to Llama Meta’s Open-Source LLM Explained.mp4 77.6 MB
  26. Llama Use Cases Build Local AI Apps & Private Assistants (Description).html 1.7 KB
  26. Llama Use Cases Build Local AI Apps & Private Assistants.mp4 122.5 MB

Description


Agentic AI & LLM: Build AI Agents with ChatGPT, Ollama & RAG
https://WebToolTip.com
Published 4/2026

Created by Deepak Rai

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: All Levels | Genre: eLearning | Language: English | Duration: 32 Lectures ( 4h 29m ) | Size: 2.47 GB
Learn Generative AI, LLMs, Prompt Engineering & Build AI Agents with Real-World Projects
What you'll learn

✓ Learn how tokens, embeddings, and context windows work in modern LLMs. Create real-world AI projects like analyzers, assistants, and automation tools.

✓ Students will learn AI, ML, LLMs, prompt engineering, RAG, vector databases, AI agents, and build real-world projects using ChatGPT, Claude, Mistral, and more.

✓ Master prompt engineering techniques for better AI responses. Work with ChatGPT, Claude, Mistral, Llama, DeepSeek, and Copilot.

✓ Understand RAG systems and how vector databases power semantic search. Build AI agents with memory, tools, and autonomous decision-making.

✓ Understand how Generative AI fits within AI and Machine Learning. Learn hosted vs open-source AI models and when to use each.
Requirements

● You don’t need advanced AI or machine learning knowledge to take this course. A basic understanding of computers and how to use the internet is enough. Knowing basic Python is helpful but not mandatory, as concepts will be explained step by step. A curiosity to learn AI, build projects, and explore new tools is the most important requirement.

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