Introduction to Data Science, 4th Edition
The definitive undergraduate textbook for data science, fully updated for the latest tools and techniques. This edition covers Python 3.12, scikit-learn 1.4, and introduces large language model integration as a data analysis tool. Written with clear explanations and hundreds of real-world examples.
Contents
- Part I: Foundations — Python programming, NumPy, Pandas
- Part II: Statistics — Probability, hypothesis testing, Bayesian inference
- Part III: Machine Learning — Regression, classification, clustering, neural networks
- Part IV: Applications — NLP, computer vision, time series, recommender systems
- Part V: Ethics & Practice — Bias, fairness, deployment, MLOps
Book Details
| Authors |
Dr. Sarah Mitchell, Prof. James Liu |
| Publisher |
Academic Press International |
| Edition |
4th (2025) |
| Pages |
842 |
| ISBN |
978-0-12-345678-9 |
| Format |
Paperback with online code repository access |
Prescribed text for: COMP2010 Data Science Fundamentals, COMP3015 Applied Machine Learning.
