 Introduction to Artificial Intelligence
 Introduction to Intelligent Agents
 The History of Artificial Intelligence
 The Building of Intelligent Agents (logic, games, search, constraint satisfaction problems)
 Applications of Artificial Intelligence (Natural Language Processing, Vision/ Robotics)
 Machine Learning Algorithms
 Solving real Artificial Intelligence problems via programming with Python
 The Fundamentals of Programming
 The Foundation of Natural Language Processing
 Data Science
 Foundation of Machine Learning (ML)
 Machine Learning (in-depth)
 Feature Engineering, the Production, and Development of ML Models
 Machine Learning case studies (real world)
 Neural Network
 Data mining and Recommender Systems
 Deep Learning
 Computer Vision
 Deep Learning case studies (real world)