Supervised learning in Python ◦ Introduction to artificial intelligence ◦ Regression vs. classification ◦ Bias vs. overfit ◦ Nearest neighbor algorithm ◦ Decision trees Supervised learning practice Unsupervised learning ◦ Basic concepts ◦ Grouping with K-stockings ◦ Grouping with closest K-neighbors ◦ Choosing the number of groups Unsupervised learning practice Machine learning pipeline ◦ Preprocessing ◦ Feature extraction ◦ Training and Prediction ◦ Assessment metrics Machine Learning Pipeline Practice