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Udemy - AI Engineering and LLM MasterClass

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Udemy - AI Engineering and LLM MasterClass (Size: 1.6 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - The AI Engineering Landscape in 2026
  1. S1_Foundations_Resource.py 12.3 KB
  1. The AI Engineering Landscape in 2026.mp4 44.9 MB
  10 - LLMOps PRODUCTION, MONITORING & COST
  11 - MULTIMODAL AI
  12 - RESPONSIBLE AI, SAFETY & GOVERNANCE
  2 - PROMPT ENGINEERING AS A DISCIPLINE
  10. Prompt Testing & Evaluation.mp4 18.2 MB
  11. Prompt Versioning & Management.mp4 25.6 MB
  3 - WORKING WITH LLM APIs
  1. Knowledge Check.html 20.5 KB
  12. OpenAI API Deep Dive.mp4 53.4 MB
  12. S3_Complete_Resource.py 15.6 KB
  12. S3_Project2_AI_Gateway.pptx 33.6 KB
  13. Anthropic Claude API.mp4 34.6 MB
  14. Google Gemini API.mp4 36.5 MB
  15. Building a Unified LLM Interface.mp4 48.6 MB
  16. Async and Concurrent API Calls.mp4 22.6 MB
  17. Response Caching & Cost Reduction.mp4 22.7 MB
  18. Logging, Observability & Debugging.mp4 23.2 MB
  4 - VECTOR DATABASES & EMBEDDINGS
  19. S4_Complete_Resource.py 11.8 KB
  19. What Are Embeddings.mp4 37.3 MB
  20. Similarity Search Deep Dive.mp4 33 MB
  21. Vector Database Landscape.mp4 24.5 MB
  22. ChromaDB Hands-On.mp4 9.6 MB
  23. Pinecone for Production.mp4 9.6 MB
  24. Chunking Strategies.mp4 16.9 MB
  5 - RAG RETRIEVAL AUGMENTED GENERATION
  2. Quiz Time!.html 20.4 KB
  25. S5_Complete_Resource.py 13 KB
  25. S5_Project4_Knowledge_Assistant.pptx 33.6 KB
  25. Why RAG The Problem It Solves.mp4 13.1 MB
  26. Naive RAG — The Basic Pipeline.mp4 13.2 MB
  27. Advanced Retrieval Techniques.mp4 14.8 MB
  28. RAG Evaluation — Measuring What Matters.mp4 17.8 MB
  29. Hybrid Search RAG.mp4 22.7 MB
  30. Corrective RAG & Self-RAG.mp4 9.8 MB
  31. GraphRAG — Knowledge Graph Enhanced Retrieval.mp4 13.7 MB
  32. Production RAG Architecture.mp4 2.7 MB
  6 - LANGCHAIN & LLM ORCHESTRATION
  33. LangChain Architecture & Philosophy.mp4 15.8 MB
  33. S6_Complete_Resource.py 25.4 KB
  33. S6_Project5_Document_Pipeline.pptx 33.6 KB
  34. Chains & LCEL.mp4 13.8 MB
  35. Memory Systems.mp4 12 MB
  36. Document Loaders & Text Splitters.mp4 9.6 MB
  37. LangChain Retrievers.mp4 19.5 MB
  38. Output Parsers & Structured Data.mp4 9.9 MB
  39. LangGraph Introduction.mp4 34.2 MB
  7 - AI AGENTS & AGENTIC SYSTEMS
  40. S7_Complete_Resource.py 18.4 KB
  40. S7_Project6_Research_Agent.pptx 33.7 KB
  40. What Are AI Agents (Description).html 716.8 B
  40. What Are AI Agents.mp4 30 MB
  41. Tool Use & Function Calling.mp4 24.2 MB
  42. LangChain Agents.mp4 8.1 MB
  43. LangGraph for Agentic Workflows.mp4 8.6 MB
  44. Multi-Agent Systems with CrewAI.mp4 11.4 MB
  45. Multi-Agent Systems with AutoGen.mp4 16.2 MB
  46. MCP — Model Context Protocol.mp4 8.6 MB
  47. Agent Reliability & Production Patterns.mp4 10.9 MB
  8 - FINE-TUNING LLMs (LoRA QLoRA)
  48. S8_Complete_Resource.py 7.9 KB
  48. S8_Project7_FineTune.pptx 33.6 KB
  48. When to Fine-Tune (And When NOT To).mp4 11.5 MB
  49. Preparing Data.mp4 9 MB
  50. Open AI Fine Tuning.mp4 7.6 MB
  51. LoRA & QLoRA.mp4 9.9 MB
  52. Evaluation Itration.mp4 18.5 MB
  9 - OPEN-SOURCE LLMs & LOCAL DEPLOYMENT
  53. OSS LLM Landscape.mp4 20.7 MB
  53. S9_Complete_Resource.py 9.1 KB
  53. S9_Project8_Local_RAG.pptx 33.5 KB
  54. Ollama Local.mp4 10.8 MB
  55. Production vLLM.mp4 10.6 MB
  56. Quantisation.mp4 18.2 MB
  57. OSS End to End.mp4 22.3 MB
  6. S2_Complete_Resource.py 17.4 KB
  6. The Anatomy of a Prompt.mp4 47.2 MB
  7. Advanced Prompting Techniques.mp4 53 MB
  8. Structured Output — Getting JSON Every Time.mp4 31.5 MB
  9. Prompt Injection & Security.mp4 32 MB
  3. Quiz Time.html 18.5 KB
  70. LLM Safety Risks & Threat Model.mp4 17.7 MB
  70. S12_Complete_Resource.py 17.1 KB
  70. S12_Project11_Responsible_AI.pptx 33.4 KB
  71. Guardrails & Content Filtering.mp4 21.8 MB
  72. Privacy, Compliance & Data Governance.mp4 19.7 MB
  73. AI Governance & Responsible Deployment.mp4 22.5 MB
  73. Cap_1_Capstone_Overview_an.pptx 36.5 KB
  73. Cap_2_Implementation_Guide.pptx 36.4 KB
  73. Cap_3_Presentation_and_Por.pptx 36.5 KB
  73. Capstone_Complete_Resource.py 19.8 KB
  65. Vision Models & GPT-4o Vision.mp4 30 MB
  66. Building Vision-Powered Applications.mp4 20.1 MB
  66. S11_Complete_Resource.py 16.8 KB
  67. Audio Whisper & Speech-to-Text.mp4 23 MB
  68. Text-to-Speech & Voice Agents.mp4 22.3 MB
  69. Multimodal RAG.mp4 22.3 MB
  58. S10_Complete_Resource.py 16.3 KB
  58. What is LLMOps.mp4 32.6 MB
  59. Prompt Versioning.mp4 19.4 MB
  60. Cost Optimization.mp4 25.3 MB
  61. Guardrails Safety.mp4 19 MB
  62. Deployment Strategies.mp4 19.6 MB
  63. Testing LLM Systems.mp4 18.9 MB
  64. LLMOps_Tools.mp4 15.4 MB
  2. How Large Language Models Work (No Maths Required).mp4 41.8 MB
  3. The LLM Ecosystem — Frontier vs Open Source.mp4 55.2 MB
  4. Development Environment Setup.mp4 34.5 MB
  5. Cost Management & Token Economics.mp4 18.9 MB

Description


AI Engineering & LLM MasterClass
https://WebToolTip.com
Published 5/2026

Created by Ganesh Ravikumar

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

Level: Intermediate | Genre: eLearning | Language: English | Duration: 73 Lectures ( 3h 56m ) | Size: 1.6 GB
LangChain • RAG • AI Agents • Fine-Tuning • Vector DBs • LLMOps • OpenAI • HuggingFace — Real Projects, Real Deployment
What you'll learn

⚡ Every section has a real deployable project

⚡ Goes beyond ChatGPT wrappers into actual engineering

⚡ Covers what companies actually hire for — RAG, Agents, Fine-tuning, LLMOps

⚡ Includes evaluation, cost optimisation, and responsible AI

⚡ 2026-current tools and frameworks only
Requirements

❗ No AI/ML background needed — we build from the ground up

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