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Introduction to Data Science

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Refund policy

The payment is 100% refundable if you cancel before the first session. The remaining tuition is pro-rated based on date of withdrawal. To request a refund, please contact [email protected]


Students should have some familiarity with basic statistical and linear algebraic concepts such as mean, median, mode, standard deviation, correlation, and the difference between a vector and a matrix. Additionally, Python is a requirement for the course. In Python, it will be helpful to know basic data structures such as lists, tuples, and dictionaries, and what distinguishes them (that is, when they should be used). Python v3 is currently used in the course.

To ensure everyone begins the course on the same page, students are encouraged to complete the following pre-work (approximately 8 hours) before the first day of instruction:

  1. Exercises 1-7, 13, 18-21, 27-35, 38,39 of Learn Python The Hard Way.
  2. Videos 1-6 of Linear Algebra review from Andrew Ng’s Machine Learning course (labeled as: III. Linear Algebra Review (Week 1, Optional).
  3. The exercises in Chapters 2 and 3 of OpenIntro Statistics.

Students must have a Github account to get access to the content. Sign-up for an account on their site is free, fast and easy.

In order to confirm a spot in the course, payment must be completed on the next page.