Teach data science using an interactive, engaging platform with real-world tools and applications
Teach data science using Python, R, or without coding!
- Data Science Foundations with Python teaches students how to use popular libraries for data science, including NumPy, pandas, matplotlib, seaborn, and scikit-learn
- Data Science Foundations with R teaches the latest tidyverse tools for computing with R
- Coding examples are integrated in Jupyter notebooks directly in the zyBook
- Need help choosing? Check out Python or R for Data Science?
- All versions include the same content and learning experience
Teach using real-world tools and datasets
- Jupyter notebooks embedded in the zyBook give students experience with professional coding tools
- Examples come from real-world datasets in business, finance, medicine, pop culture, science, and technology
- Real-world case studies model the data science lifecycle from end-to-end throughout the course
Focus on concepts first, computing second
- Conceptual ideas in data science are taught and reinforced first using our award-winning “Say-Show-Ask” pedagogy
- Coding examples expand and explore applications of data science with real datasets
Add your own Jupyter notebooks directly in the zyBook
- Instructors can now add custom Jupyter notebooks directly in the zyBooks platform!
- Use custom content to host assignments and projects, expand on existing content, or give additional detail
Leverage zyBooks across the data science program
Take advantage of other zyBooks to expand and scale up your data science program, including:
- Python Programming
- Applied Statistics with Data Analytics
- Introduction to Statistical Investigations
- Machine Learning
Keep your classes up-to-date with the latest in artificial intelligence
- In Data Science Foundations, students will learn about major applications of artificial intelligence, including computer vision, natural language processing, and large language models (LLMs). Data Science Foundations also covers ethical use and implications of AI.
- Machine Learning covers the building blocks of deep learning and AI applications, with examples using Keras, PyTorch, and TensorFlow.
- With zyBooks’ continuous publishing model, content is regularly updated as new AI methods and tools develop.