Covers the basics of Machine Learning, including recognizing hand-written digits, supervised classification, decision boundaries, and polynomial curve fitting.
Introduces Natural Language Processing (NLP) and its applications, covering tokenization, machine learning, sentiment analysis, and Swiss NLP applications.