Contents

Book I – Prelude to Data Understanding (with J. Schellinck, C. Ma, and F. Donzelli)
     1. Programming Primer
     ??. Linear Algebra
     ??. Multivariate Calculus
     ??. Numerical Methods
     2. Optimization
     3. Probability and Applications
     4. Introductory Statistical Analysis
     ??. Regression Analysis
     ??. Design of Experiments
     5. Survey Sampling Methods
     ??. Time Series and Forecasting
     ??. Simulations

Book II – Fundamentals of Data Insight (with J. Schellinck)
     6. Non-Technical Aspects of Data Work
     7. Data Science Basics
     8. Data Preparation
     9. Data Visualization and Data Exploration
     10. Data Engineering and Management

Book III – Spotlight on Machine Learning
     11. Machine Learning 101
     12. Regression and Value Estimation
     13. Spotlight on Classification
     14. Spotlight on Clustering
     15. Feature Selection and Dimension Reduction

Book IV – Special Topics in Data Analysis
     16. Anomaly Detection and Outlier Analysis
     17. Web Scraping and Automated Data Collection
     18. Bayesian Data Analysis
     ??. Data Science with Streams
     ??. Text Analysis and Text Mining
     ??. Deep Learning
     ??. Natural Language Processing
     19. Queueing Systems

Book V – Advanced Topics in Data Analysis
     ??. Network Data Analysis
     ??. Recommender Engines
     ??. Big Data and Parallel Computing
     ??. Reinforcement Learning
     ??. Computer Vision and Image Analysis
     ??. Causality Modeling