Contents

• Setup
  • vscode terminal settings
  • Version Control using Git
• Foundations
  • Basics of AI and ML
  • Types of ML models
  • modeling guidelines
• Supervised Learning
  • Linear Regression
  • Classification models
  • Tree models
  • Neural networks
  • Evaluating machine learning models
• Un-Supervised Learning
  • Clustering
• Computer Vision
  • Intro to Computer Vision
• Time Series
  • Forecasting
  • Anomaly Detection
• Generative Models
  • RAG
  • Agentic AI