❖ Introduction to Artificial Intelligence
❖ History of Artificial Intelligence
❖ Applications of Machine Learning
❖ Building intelligent agents (search, games, logic, constraint
satisfaction problems)
❖ Pre-Program Preparation
❖ Statistics Essentials
❖ Machine Learning
❖ Natural Language Processing
❖ Text mining using NLP
❖ Neural Networks & Deep Learning
❖ Graphical Models
❖ LSI and mining
✓ Object recognition using Al
✓ Sentimental analysis using Al
✓ Naïve Bayes theorem-based problem solving
✓ Solving real Al problems through programming with Python