• Mathematics preliminary: probability + statistics

• Data mining

• Statistics I: Analysis

• Visualization

• Linear algebra and dimensionality reduction

• Linear regression

• Supervised learning

• Unsupervised learning

• Implementing machine learning techniques, broadly speaking supervised and unsupervised learning methods and dimensionality reduction using SciKit-Learn

• Introduction to deep learning

• Natural language processing

• Time series analysis using Pandas

• Network analysis

• Bayesian inference and introduction to Bayesian networks