More than at any other time in our history, we are living through a paradigm shift in how we think about data. Advances in computing power, algorithms for data modeling and machine learning, coupled with unparalleled access to vast quantities of data has transformed disciplines across the sciences, social sciences, and humanities. The Minor in Applied Data Science will help students learn fundamental data science methodologies drawn from computing and statistics and provide opportunities to apply these methodologies to datasets, problem domains, and explorations in many disciplines of study in Arts & Science. Understanding the human and ethical contexts and communicating results of data science methodologies will appear in courses throughout the program.

The minor is designed to complement programs in other areas with opportunities for data science applications (see program requirements for pertinent programs). This program is designed to be accessible to students who have never done any computer programming or statistics before, or who haven’t taken high school or university calculus. All skills necessary to succeed in the program are taught in our courses. Most students who are interested in this program should start by choosing one of our three introductory, interdisciplinary data science courses: EEB125H1, GGR274H1, or ENG286H1, which introduce data science skills such as computer programming, statistical reasoning, and data visualization within the context of a particular discipline. Students then proceed to take a suite of key computer science and statistics courses that reinforce and extend these skills, with an emphasis on applications to real-world problems. Finally, in later years students will choose from a wide variety of courses drawn from across the Faculty of Arts & Science. These upper-year courses will provide the opportunity to discuss and analyze the human contexts of data science, and to apply data science methodologies in discipline-specific contexts.