6 Weeks


2 Nights per Week



Learn through Application and Teamwork

Applied Math with Python covers essential mathematical principles that are necessary for success as a data scientist. This course is an ‘applied math’ course: principles and ideas are introduced and then quickly applied using Python. You survey topics from calculus, linear algebra, probability, and statistics literally ‘hands-on’ (the keyboard) and visually (as you visualize data and analyze Python). Classes are offered both on campus and online and held Mondays and Wednesdays from 5:30-8pm Pacific Time, so you can maintain your schedule without compromising the quality of your education. The class is very active and immersive, as you work with peers to solve math problems guided by your instructor, a former CERN physicist.

Expand on your Python Skills

This workshop is for those who want to get ready for the Data Science Immersive program and would like more help with math and taking Python to the next level. The course will help blend your understanding of math with your ability to code, which is an essential trait of successful immersive students.

Mathematical Foundations of Data Science

Building upon your python skills, you’ll explore topics like linear algebra, differential calculus, statistics, and probability.

Entrance Exam

An entrance exam is required to demonstrate proficiency at the graduate level of Python Fundamentals OR Data Science Premium Prep. This requires comfort instantiating and manipulating strings, lists, sets, and dictionaries, and creating single functions with returns.

What You'll Learn

Survey of Mathematics

We’ll refresh you on calculus, linear algebra, probability, and statistics. If you’ve never taken a course in any, you’ll learn enough to know where you might need to dig in.

Applied Python Knowledge

No more toy problems, no more playing around. Use computers for what they were designed for: the heaving lifting of advanced math.

Data Science Libraries

Expand your knowledge of popular data science libraries including Matplotlib, Pandas, NumPy.

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