Volume 1: Prelude to Data Understanding 846 pages | October 2023 Programming Primer; Multivariate Calculus for Data Analysis; Overview of Linear Algebra; Basics of Numerical Methods; A Survey of Optimization; Probability and Applications; Introductory Statistical Analysis; Classical Regression Analysis; Time Series and Forecasting; Survey Sampling Methods; The Design of Experiments; Simulations and Modeling |
Volume 2: Fundamentals of Data Insight310 pages | January 2024 Non-Technical Aspects of Quantitative and Data Work; Data Science Basics; Data Preparation; Web Scraping and Automatic Data Collection; Data Engineering and Data Management; Data Exploration and Data Visualization |
Volume 3: Spotlight on Machine Learning 468 pages | July 2024 Introduction to Machine Learning; Regression and Value Estimation; Focus on Classification and Supervised Learning; Focus on Clustering; Feature Selection and Dimension Reduction |
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Volume 4: Techniques of Data Analysis (coming in 2024) Queueing Systems; Bayesian Data Analysis; Anomaly Detection and Outlier Analysis; Text Analysis and Text Mining; Mining Data Streams; (Social) Network Data Analysis |
Volume 5: Special Topics in D.S. and A.I. (coming in 2025) What's the Big Deal with Big Data?; A Deep Learning Launchpad; Natural Language Processing; Reinforcement Learning and A.I.; Recommender Engines; Image Analysis and Computer Vision; Causality and Belief Networks |
The Practice of Data Visualization 387 pages | July 2023 with J. Schellinck and S. Davies |