Principles of Data Science
Suitable Age Group: Ages 18–21
Grade Reference
| 🇺🇸 United States | College Freshman – College Senior |
| 🇬🇧 United Kingdom | University Year 1 – University Year 4 |
| 🇮🇳 India | B.Sc. Year 1 – B.Sc. Year 4 |
| 🇳🇬 Nigeria | University Year 1 – University Year 4 |
| 🇿🇦 South Africa | University Year 1 – Honours |
| 🇦🇺 Australia | University Year 1 – Honours |
| 🇨🇦 Canada | University Year 1 – University Year 4 |
About This Textbook
An introductory text covering the principles and practices of data science, designed for a broad audience including students pursuing computer science, business, science, social science, and related fields. Topics include data wrangling, data visualization, statistical analysis, machine learning, and ethical considerations in data science.
Table of Contents
Introduction to Data Science — Data Types, Sources, and Collection — Data Wrangling and Preprocessing — Exploratory Data Analysis — Data Visualization — Statistical Analysis — Probability and Distributions — Regression and Prediction — Machine Learning — Ethics in Data Science
