Content:
– Motivational introduction;
– What is AI: the 4 approaches;
– Explicit / implicit approaches;
– Machine learning and its types;
– Supervised learning (demonstration using k-nearest neighbours);
– Unsupervised learning (demonstration using k-means);
– Reinforcement learning;
– Local and global generalization;
– Search methods (demonstration using naïve search for Sudoku);
