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Foundations of Data: Data Science, Student Print and Online Course, 1-year subscription

Foundations of Data: Data Science, Student Print and Online Course, 1-year subscription

National Edition
MHID: 1265971366 | ISBN 13: 9781265971366
Grades: 9 - 12

Payment Options: During checkout, you can pay with a P.O. (simply enter the number), Credit Card, or PayPal.

Equip high school students with the knowledge and skills to thrive in a data-driven world. 

Foundations of Data: Data Science introduces learners to essential concepts in data collection, analysis, visualization, and prediction. Students explore real-world data challenges through hands-on projects using Python and industry-standard tools, gaining experience with statistical analysis, machine learning, and data modeling techniques. The course provides a strong foundation for students pursuing future studies or careers in data science and analytics.


Foundations is an innovative series of titles designed for high school students, each covering a specific area of the digital world. These key features of every Foundations program bring skills to life:

  • Clear instruction and active learning: Students thrive in their learning when presented with well-defined goals, clear instruction, relevant examples, hands-on activities, and project-based learning.
  • Timely and relevant coverage: Content aligns with the latest industry practices, preparing students for future careers.
  • Complete teacher support: Educators prepare efficiently with a print teacher’s edition, lesson plans, lesson guides, and pre-built assessments.
  • Flexible delivery: Students benefit from a hardbound textbook or use the digital resources complete with an eBook, an adaptive SmartBook®, assessment, videos, and more.



Students using Foundations of Data: Data Science will:
  • Learn how to collect, clean, and analyze data using tools like Python, Pandas, NumPy, and Jupyter Notebook.
  • Explore key data science concepts, including statistical analysis, data visualization, predictive modeling, and optimization.
  • Build and present data-driven insights through real-world projects focused on solving practical problems.
  • Develop foundational skills for future careers in data analytics, machine learning, and data-driven decision-making.