1. Introduction
2. Communicating Effectively and Earning Trust
3. Data Science Project Planning
4. An Overview of Data
5. Computing Preliminaries and Setup
6. Data Processing
7. Data Storage and Retrieval
8. Mathematics Preliminaries
9. Statistics Preliminaries
10. Data Transformation
11. Exploratory Data Analysis
12. An Overview of Machine Learning
13. Modeling with Linear Regression
14. Classification with Logistic Regression
15. Clustering with K-Means
16. Elements of Reproducible Data Science
17. Model Risk
18. Next Steps
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Biography
Adam P. Tashman has been working in data science for over twenty years. He is Associate Professor of Data Science at the University of Virginia School of Data Science. He is currently Director of the Capstone program, and he was formerly Director of the Online Master's of Data Science program. He was the School of Data Science Capital One Fellow for the 2023-2024 academic year. Dr. Tashman won multiple awards from Amazon Web Services, where he advised education and government technology companies on best practices in machine learning and artificial intelligence. Dr. Tashman lives in Charlottesville, VA with his wonderful wife Elle and daughter Callie.
