How Much Math Do You Need for Data Science?

MOOCs (Massive Open Online Courses) are awesome, but they do not provide real academic course credit for their courses. If you plan to go for a B.A. or M.A. with a Data Science concentration, you will not be able to say "Oh, I took all my calculus courses from a MOOC" - you need these courses in your academic portfolio.

• edX
• Coursera
• Udacity
• Khan Academy
• MIT Open Courseware

We invite you to explore our Distance Calculus courses in more detail via the links above, or perhaps the movies below.

Academic Credits from Distance Calculus

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Data Science & Distance Calculus

Data Science can best be described as a "a cross between a programmer and a mathematician/statistician".

This topic has many names, all being equivalent:

• Data Science
• Applied Statistics
• Programmer+Mathematician
• Big Data

If you wish to become a Data Scientist, you will need to develop both strong programming skills, and have a very strong mathematics background.

Distance Calculus @ Roger Williams University can help prepare you for a study of Data Science - either for a degree in Data Science or perhaps a certificate - by helping you complete the core mathematics courses necessary for starting a Data Science degree or certificate.

There are no short-cuts you can do with going into Data Science. You just can't learn Python and then pretend you are a Data Scientist because you watch a few videos on running data sets through Python! You NEED a very strong mathematics background that includes ALL of the following courses:

• DMAT 253 - Calculus I - 4 credits
• DMAT 263 - Calculus II - 4 credits
• DMAT 355 - Multivariable Calculus - 4 credits
• DMAT 321 - Differential Equations - 3 credits
• DMAT 335 - Linear Algebra - 3 credits
• DMAT 311 - Probability Theory - 3 credits