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Udemy - AI & LLM Engineering Mastery GenAI, RAG Complete Guide (2.2025)

UdemyEngineeringMasteryGenAICompleteGuide2025

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收录时间：2026-03-12

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文件列表：

  1. 19. HANDS-ON - Building LLM Applications with LangChain/9. Voice Assistant RAG System - Walkthrough and Demo.mp4239.77 Mb
  2. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/13. Hands-on - Re-ranking Implementation with Cohere - Full Implementation.mp4222.7 Mb
  3. 23. Fine-tuning LLMs/7. HANDS-ON - Fine-tuning an OpenAI Model - Full Walkthrough.mp4205.27 Mb
  4. 15. Vector Databases and Embeddings - Deep Dive/4. Why Vector Databases.mp4204.3 Mb
  5. 19. HANDS-ON - Building LLM Applications with LangChain/2. News Summarizer - Full Implementation.mp4200.53 Mb
  6. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/7. Hands-on- Setting up the Workflow and Code Walkthrough.mp4194.04 Mb
  7. 18. LLM Tools and Frameworks - LangChain Deep Dive/14. Hands-on Full RAG System QA Bot Using LangChain.mp4177.79 Mb
  8. 12. Context & Memory Management for LLMs - Deep Dive/3. HANDS-ON - Adding Memory and Context to Chatbox.mp4170.42 Mb
  9. 13. Logging in LLM Applications - Deep Dive/3. HANDS-ON - Chatbot with Logging.mp4169.33 Mb
  10. 15. Vector Databases and Embeddings - Deep Dive/7. Vector Databases & Embeddings - Full Overview.mp4158.06 Mb
  11. 21. Multimodal RAG - Deep Dive/4. Multimodal RAG - Overview & Motivation and Benefits - How it Works.mp4153.85 Mb
  12. 19. HANDS-ON - Building LLM Applications with LangChain/5. Youtube Video Summarizer Class Setup and Walkthrough.mp4149.2 Mb
  13. 12. Context & Memory Management for LLMs - Deep Dive/2. What is Context and Memory Management - Deep Dive.mp4143.84 Mb
  14. 16. HANDS-ON - RAG PDF Workflow - Build RAG Workflows Deep Dive/4. HANDS-ON - Building and Showcasing the RAG Workflow.mp4143.05 Mb
  15. 15. Vector Databases and Embeddings - Deep Dive/12. The Top 5 Vector Databases - Overview.mp4142.55 Mb
  16. 22. AI Agents & Agentic Workflows - Deep Dive/26. Adding Nodes and Edges and Running our Agent.mp4140.82 Mb
  17. 24. Fine-Tuning Technique - LoRA Deep Dive/4. Hands-on - Training Models - LoRA and PEFT.mp4136.12 Mb
  18. 08. LLMs (Large Language Models) - Fundamentals - A Deep Dive/5. HANDS-ON - Create a Simple LLM from the Transformers Library - Simple.mp4135.86 Mb
  19. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/72. Building an Image Watermarker in Python - Part 1.mp4130.31 Mb
  20. 22. AI Agents & Agentic Workflows - Deep Dive/1. AI Agents Deep Dive - A Full Overview.mp4127.33 Mb
  21. 15. Vector Databases and Embeddings - Deep Dive/15. Chroma Database workflow.mp4126.82 Mb
  22. 23. Fine-tuning LLMs/2. Fine-tuning Techniques - Overview.mp4121.43 Mb
  23. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/77. Plotting a Graph with CSV Data.mp4118.53 Mb
  24. 22. AI Agents & Agentic Workflows - Deep Dive/25. Creating All Nodes - Functions.mp4116.83 Mb
  25. 17. HANDS-ON - Build a PDF RAG System with Text Chunking/4. Testing the PDF RAG System.mp4116.4 Mb
  26. 22. AI Agents & Agentic Workflows - Deep Dive/5. Build our First AI Agent - Creating the Agent Class and Prompt.mp4113.83 Mb
  27. 19. HANDS-ON - Building LLM Applications with LangChain/6. Youtube Video Summarizer Q&A - Testing the Workflow.mp4113.7 Mb
  28. 11. Ollama & Open-Source Models - Complete Guide/3. Ollama Deep Dive - Ollama Overview - What is Ollama and Advantages.mp4112.36 Mb
  29. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/73. Generating the Watermarked Images.mp4112.25 Mb
  30. 22. AI Agents & Agentic Workflows - Deep Dive/7. Passing Complex Queries Through the Agent.mp4111.12 Mb
  31. 17. HANDS-ON - Build a PDF RAG System with Text Chunking/3. Setting up the SimpleRAGSystem Class and Methods.mp4110.64 Mb
  32. 15. Vector Databases and Embeddings - Deep Dive/6. Traditional vs. Vector Databases - Limitations and challenges.mp4110.47 Mb
  33. 06. Deep and Machine Learning Deep Dive/2. Deep Learning Key Aspects.mp4109.43 Mb
  34. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/3. Deep Dive into Each Naive RAG Drawbacks.mp4107.01 Mb
  35. 22. AI Agents & Agentic Workflows - Deep Dive/20. Adding Memory to Our Agent State.mp4106.65 Mb
  36. 22. AI Agents & Agentic Workflows - Deep Dive/15. Building a Simple Agent with LangChain.mp4106.38 Mb
  37. 21. Multimodal RAG - Deep Dive/9. Finish the Multimodal Search System.mp4104.11 Mb
  38. 11. Ollama & Open-Source Models - Complete Guide/8. Ollama Model Parameters Deep Dive.mp4103.76 Mb
  39. 22. AI Agents & Agentic Workflows - Deep Dive/8. First Agent - Using a Loop to Automate our Agent.mp4102.85 Mb
  40. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/68. Hands-on - File Organizer.mp4102.59 Mb
  41. 06. Deep and Machine Learning Deep Dive/3. Deep Neural Network Dissection - Full Dive with Analogies.mp4101.4 Mb
  42. 15. Vector Databases and Embeddings - Deep Dive/10. Vector Databases Use Cases.mp4101 Mb
  43. 17. HANDS-ON - Build a PDF RAG System with Text Chunking/2. PDF and Chunk Processing and Chunk Overlap - Deep Dive.mp4100.57 Mb
  44. 06. Deep and Machine Learning Deep Dive/1. Deep and Machine Learning Deep Dive - Overview and Breakdown.mp4100.54 Mb
  45. 15. Vector Databases and Embeddings - Deep Dive/21. Using OpenAIs Embedding API to Create Embedding in ChromaDB.mp497.23 Mb
  46. 12. Context & Memory Management for LLMs - Deep Dive/1. HANDS-ON - Context and Memory Management Overview.mp497.13 Mb
  47. 22. AI Agents & Agentic Workflows - Deep Dive/27. Adding a GUI to the Agent with Streamlit.mp496.31 Mb
  48. 22. AI Agents & Agentic Workflows - Deep Dive/11. LangGraph - Overview & Key Concepts.mp496.13 Mb
  49. 18. LLM Tools and Frameworks - LangChain Deep Dive/8. Hands-on Embeddings and Retriever with FAISS VectorStore.mp494.16 Mb
  50. 08. LLMs (Large Language Models) - Fundamentals - A Deep Dive/6. HANDS-ON - Hands-on Enhanced Transformers LLM.mp493.74 Mb
  51. 18. LLM Tools and Frameworks - LangChain Deep Dive/3. LangChain Setup and ChatModel.mp492.54 Mb
  52. 11. Ollama & Open-Source Models - Complete Guide/17. Ollama Model Running Under Msty App.mp492.28 Mb
  53. 24. Fine-Tuning Technique - LoRA Deep Dive/6. Creating an API Service to Interface with Our Fine-tuned Models.mp491.84 Mb
  54. 15. Vector Databases and Embeddings - Deep Dive/30. Generating Embeddings from Documents and Insert to Vector Database.mp491.62 Mb
  55. 16. HANDS-ON - RAG PDF Workflow - Build RAG Workflows Deep Dive/5. HANDS-ON - RAG Workflow with UI - Streamlit.mp488.73 Mb
  56. 24. Fine-Tuning Technique - LoRA Deep Dive/5. Running LoRA Model Fine-tuning and Testing.mp488.1 Mb
  57. 15. Vector Databases and Embeddings - Deep Dive/19. Chroma Vector Database - Persisting Data and Saving.mp486.1 Mb
  58. 21. Multimodal RAG - Deep Dive/7. Visual Explanation Why Multimodal Search is so Powerful.mp485.45 Mb
  59. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/10. Re-Ranking & Cross-encoder and Bi-encoders - Overview.mp485.38 Mb
  60. 15. Vector Databases and Embeddings - Deep Dive/3. Introduction to Vector Databases - Full Overview.mp485.33 Mb
  61. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/49. Inheritance - Create an Ebook - Child Class.mp481.81 Mb
  62. 24. Fine-Tuning Technique - LoRA Deep Dive/2. LoRA Deep Analysis.mp480.4 Mb
  63. 18. LLM Tools and Frameworks - LangChain Deep Dive/2. What is LangChain and and Main Components.mp479.81 Mb
  64. 13. Logging in LLM Applications - Deep Dive/2. Logging in LLM Applications and Logging Life Cycle.mp479.26 Mb
  65. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/52. The Object Class - Overview.mp479.06 Mb
  66. 21. Multimodal RAG - Deep Dive/2. RAG & Multimodal RAG - Recap and Overview.mp477.91 Mb
  67. 17. HANDS-ON - Build a PDF RAG System with Text Chunking/1. PDF RAG Workflow - Architecture Overview.mp477.65 Mb
  68. 21. Multimodal RAG - Deep Dive/14. Setting up the RAG Workflow.mp477.01 Mb
  69. 15. Vector Databases and Embeddings - Deep Dive/29. Loading all Documents.mp476.67 Mb
  70. 24. Fine-Tuning Technique - LoRA Deep Dive/9. Full LoRA Workflow - Train and Chat with Fine-tuned Models.mp475.86 Mb
  71. 16. HANDS-ON - RAG PDF Workflow - Build RAG Workflows Deep Dive/3. Setting up the Embedding Model Class.mp475.59 Mb
  72. 08. LLMs (Large Language Models) - Fundamentals - A Deep Dive/1. LLMs - Overview.mp475.5 Mb
  73. 11. Ollama & Open-Source Models - Complete Guide/4. Ollama Key Features and Use Cases.mp474.96 Mb
  74. 08. LLMs (Large Language Models) - Fundamentals - A Deep Dive/2. The Transformer Architecture - Fundamentals.mp474.84 Mb
  75. 15. Vector Databases and Embeddings - Deep Dive/32. Using OpenAI LLM to Generate Response - Full Workflow.mp474.66 Mb
  76. 15. Vector Databases and Embeddings - Deep Dive/20. Creating an OpenAI Embeddings - Raw without Chroma.mp474.3 Mb
  77. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/2. What is RAG and Naive RAG Overview and Pitfalls - Motivation.mp473.95 Mb
  78. 15. Vector Databases and Embeddings - Deep Dive/22. Vector Databases Metrics and Data Structures.mp473.25 Mb
  79. 22. AI Agents & Agentic Workflows - Deep Dive/17. Adding Tools to our Basic LangGraph Agent.mp473.24 Mb
  80. 22. AI Agents & Agentic Workflows - Deep Dive/18. Adding tools to the Agent - Part 1.mp473.17 Mb
  81. 14. RAG - Retrieval-Augmented Generation - Deep Dive/4. RAG Deep Dive - Full Diagram Walkthrough.mp471.65 Mb
  82. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/69. Python Virtual Environment and PIP.mp470.73 Mb
  83. 15. Vector Databases and Embeddings - Deep Dive/16. Creating a ChromaDB and Adding Documents and Querying.mp470.39 Mb
  84. 22. AI Agents & Agentic Workflows - Deep Dive/21. Adding Human-in-the-loop to the AI Agent.mp469.35 Mb
  85. 21. Multimodal RAG - Deep Dive/8. HANDS-on Multimodal Search System setup - Create Embeddings from Images.mp468.79 Mb
  86. 21. Multimodal RAG - Deep Dive/3. RAG Benefits and Practical Applications.mp467.95 Mb
  87. 22. AI Agents & Agentic Workflows - Deep Dive/6. First AI Agent - Running our First Agent and Seeing the Results.mp467.78 Mb
  88. 15. Vector Databases and Embeddings - Deep Dive/31. Getting the Relevant Chunks when Given a Query.mp467.67 Mb
  89. 15. Vector Databases and Embeddings - Deep Dive/28. Vector Databases and LLM - Deep Dive.mp467.44 Mb
  90. 06. Deep and Machine Learning Deep Dive/6. Activation Functions - Deep Dive with Analogies.mp465.55 Mb
  91. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/34. Hands-on Dream Travel Itinerary Program - Filling a Dictionary with User Input.mp465.4 Mb
  92. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/5. Hands-on - Query Expansion with Multiple Queries - Generate Multiple Queries.mp464.81 Mb
  93. 18. LLM Tools and Frameworks - LangChain Deep Dive/13. Hands-on - Simple RAG System with Chat and LangChain Chains.mp464.72 Mb
  94. 22. AI Agents & Agentic Workflows - Deep Dive/10. Agent Introduction - Section Summary.mp464.37 Mb
  95. 20. Advanced RAG Techniques - Naive vs Advanced RAG Techniques/8. Query Expansion Full RAG Workflow.mp464.28 Mb
  96. 18. LLM Tools and Frameworks - LangChain Deep Dive/7. Hands-on Text Splitting and Cleaning.mp463.67 Mb
  97. 24. Fine-Tuning Technique - LoRA Deep Dive/1. LoRA Introduction - Benefits.mp463.43 Mb
  98. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/67. Hands-on - Writing and Reading - Countries to JSON file.mp462.91 Mb
  99. 05. OPTIONAL - Python Deep Dive - Master Python Fundamentals/32. Hands-on - Quiz Game.mp462.18 Mb
  100. 21. Multimodal RAG - Deep Dive/10. HANDS-ON - Multimodal Recommender System - Overview.mp461.51 Mb
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