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  1 - Introduction

   2 -Traditional Programming vs Machine Learning.mp4

   4 -Unsupervised Learning.mp4

   6 -Feature Engineering and Dataset Splitting.mp4

   9 -Hyperparameter Tuning and Balancing BiasVariance.mp4

  2 - Introduction to Machine Learning Algorithms

   2 -Linear Regression.mp4

   4 -Decision Tree.mp4

   6 -Support Vector Machines (SVMs).mp4

   8 -Boosting Algorithms.mp4

  3 - Large Language Models

   2 -What and How of Large Language Models (LLMs).mp4

   4 -Transformers and Attention Mechanism.mp4

   6 -Prompt Engineering.mp4

   8 -Retrieval Augmented Generation (RAG).mp4

  4 - Introduction to Agentic AI

   2 -What is Agentic AI.mp4

   4 -Memory and Planning.mp4

   6 -Multi Agents, Examples and Challenges.mp4

   8 -Module Summary.mp4

  5 - Introduction to MLOps

   2 -Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4

   4 -MLOps Case Studies - Learning from the Pioneers.mp4

   6 -Emergence of a MLOps Engineer.mp4

  Bonus Resources.txt