Essential Math for Data Science?

Answer: A lot!
To even study Data Science, you need start off being a mathematician/statistician, which means you need a very solid foundation in university mathematics, starting with the following undergraduate, lower-division courses:

• Calculus I
• Calculus II
• Multivariable Calculus
• Differential Equations
• Linear Algebra
• Probability Theory (Calculus-Based Statistics)

You may have searched around the internet looking for math/calculus-level courses to build up your math skills in preparation for Data Science. There certainly are excellent (free!) courses online via MOOCs (Massive Open Online Courses). However, you will want to have all of the above courses on real, transferable Academic transcripts to prove you have completed these courses, with letter grades, not just say "I took these courses from a MOOC". You need real credentials as a mathematician 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.

Data Science & Distance Calculus

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Academic Credits from 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