Essential Math for Data Science?
Question: How much math do you need to study 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. 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
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:
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:
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
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Distance Calculus - Student Reviews
Posted: Apr 6, 2020
Courses Completed: Multivariable Calculus, Differential Equations
I took Multivariable and Diff Eq during the summer. The DiffEq course was awesome - very useful for my physics and engineering course. I was unsure about Mathematica at first, but I got the hang of it quickly. Thank you Distance Calculus!
Transferred Credits To: University of Oregon
Posted: May 17, 2025
Courses Completed: Calculus II
Dr. Curtis's lessons were well taught, and livemath wasn't too bad once you understood it. Some of the assignments were pretty difficult and required some more explanation, which was hard to get outside of the given lessons.
Email: colindonahoe4@gmail.com
Transferred Credits To: Saint Joseph's Univesity
Posted: May 18, 2025
Courses Completed: Probability Theory
A great way to learn probability theory through visualizations, code, and math. Rather than just solving equations through pencil and paper, this course helped me to see how how probability distributions form and behavior through simulations and visuals. I would recommend this course to anyone looking for a way a more interactive way to learn mathematics and at their own pace.
Transferred Credits To: none yet
Posted: Jan 28, 2026
Courses Completed: Calculus I
After two failed attempts at my university, this course helped me understand Calculus. The live maths tool along with Dr. Curtis were especially helpful, allowing me to visualize concepts and expand my understanding. The explanations were clear, the examples practical, and I could learn at my own pace, which built my confidence. Thank you.
Transferred Credits To: University of Namibia
Posted: Dec 18, 2025
Courses Completed: Differential Equations
Transferred Credits To: Saint Joseph High School
Posted: Nov 20, 2025
Courses Completed: Precalculus, Applied Calculus
Great course. Professor Curtis and the TAs graded quickly and gave really helpful feedback that made the class feel smooth and manageable. Definitely recommend it.
Transferred Credits To: Binghamton University (School of Managment)
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