Mapping the Course for Future AI Engineers
Mathematical foundations: Linear algebra, calculus, probability, and statistics.
Basics of Python programming, a key language for AI and ML.
Essential data structures and algorithms for AI and ML.
Covers AI basics: Search, reasoning, planning, learning, and natural language processing.
Principles of ML: Supervised learning, unsupervised learning, and reinforcement learning.
In-depth exploration of neural networks and deep learning techniques.
Integration of robotics principles with AI technologies.