Does Data Science Require Calculus?
Answer: Absolutely!In order to study Data Science, you need to become 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.
Freshman Math Courses
- Applied Calculus for Business [3 credits] [3CR]
- Applied Calculus for Life Science [3 credits] [3CR]
- Calculus I[4 credits] [4CR]
- Calculus II[4 credits] [4CR]
Sophomore Math Courses
- Multivariable Calculus III [4 credits] [4CR]
- Differential Equations [3 credits] [3CR]
- Linear Algebra [4 credits] [4CR]
- Probability Theory [3 credits] [3CR]
Honors Math Courses
- Honors Calculus I [5 credits] [5CR]
- Honors Calculus II [5 credits] [5CR]
- Honors Calculus I+II for Data Science [5 credits] [5CR]
- Honors Multivariable Calculus [5 credits] [5CR]
- Honors Differential Equations [4 credits] [4CR]
- Honors Linear Algebra [5 credits] [5CR]
- Honors Linear Algebra for Data Science [5 credits] [5CR]
Lower Division Math Courses
- Precalculus with Trigonometry [4 credits] [4CR]
- Introductory Statistics [4 credits] [4CR]
- Finite Mathematics [3 credits] [3CR]
- Discrete Mathematics [4 credits] [4CR]
Upper Division Math Courses
- Computational Abstract Algebra [4 credits] [4CR]
- Computational Differential Geometry [4 credits] [4CR]
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:
- 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
Freshman Math Courses
- Applied Calculus for Business [3 credits] [3CR]
- Applied Calculus for Life Science [3 credits] [3CR]
- Calculus I[4 credits] [4CR]
- Calculus II[4 credits] [4CR]
Sophomore Math Courses
- Multivariable Calculus III [4 credits] [4CR]
- Differential Equations [3 credits] [3CR]
- Linear Algebra [4 credits] [4CR]
- Probability Theory [3 credits] [3CR]
Honors Math Courses
- Honors Calculus I [5 credits] [5CR]
- Honors Calculus II [5 credits] [5CR]
- Honors Calculus I+II for Data Science [5 credits] [5CR]
- Honors Multivariable Calculus [5 credits] [5CR]
- Honors Differential Equations [4 credits] [4CR]
- Honors Linear Algebra [5 credits] [5CR]
- Honors Linear Algebra for Data Science [5 credits] [5CR]
Lower Division Math Courses
- Precalculus with Trigonometry [4 credits] [4CR]
- Introductory Statistics [4 credits] [4CR]
- Finite Mathematics [3 credits] [3CR]
- Discrete Mathematics [4 credits] [4CR]
Upper Division Math Courses
- Computational Abstract Algebra [4 credits] [4CR]
- Computational Differential Geometry [4 credits] [4CR]
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Distance Calculus - Student Reviews
Date Posted: Jul 12, 2021
Review by: Henry R.
Courses Completed: Multivariable Calculus
Review: Fantastic and unique course, particularly good for visual/spatial thinkers. The course forces you to develop a real conceptual understanding of the math concepts, as opposed to just teaching math formulas like other courses tend to do. There is a steep learning curve early on to get used to the software and the kind of course this is. Ultimately, I feel like what I learned will allow me to actually use the math and build upon it in the future. If you care about learning, rather than just passing a requirement, this is a great course for you.
Transferred Credits to: Harvard University
Date Posted: Jul 22, 2021
Review by: Emma C.
Courses Completed: Linear Algebra
Review: This was a great course. Flexible and informative with a great professor. It's a great option if you need to fill a prerequisite fast or if you enjoy working at your own pace.
Transferred Credits to: University of Virginia
Date Posted: Jan 12, 2020
Review by: Brian Finley
Courses Completed: Calculus II
Review: I took Calculus II through Distance Calculus and can't recommend it enough. Being able to take the course at my own pace while I was working full time was tremendously helpful, especially since I hadn't taken a math course for 5 years prior. The instruction was excellent and the software they used to teach the course was intuitive and facilitated the learning process very well. This calc II class enabled me to take multivariable calc, linear algebra, and real analysis at Harvard University's extension school, which ultimately qualified me for the economics PhD program that I will graduate from next year. 8 years on, I'm still grateful to Professor Curtis and Distance Calculus.
Freshman Math Courses
- Applied Calculus for Business [3 credits] [3CR]
- Applied Calculus for Life Science [3 credits] [3CR]
- Calculus I[4 credits] [4CR]
- Calculus II[4 credits] [4CR]
Sophomore Math Courses
- Multivariable Calculus III [4 credits] [4CR]
- Differential Equations [3 credits] [3CR]
- Linear Algebra [4 credits] [4CR]
- Probability Theory [3 credits] [3CR]
Honors Math Courses
- Honors Calculus I [5 credits] [5CR]
- Honors Calculus II [5 credits] [5CR]
- Honors Calculus I+II for Data Science [5 credits] [5CR]
- Honors Multivariable Calculus [5 credits] [5CR]
- Honors Differential Equations [4 credits] [4CR]
- Honors Linear Algebra [5 credits] [5CR]
- Honors Linear Algebra for Data Science [5 credits] [5CR]
Lower Division Math Courses
- Precalculus with Trigonometry [4 credits] [4CR]
- Introductory Statistics [4 credits] [4CR]
- Finite Mathematics [3 credits] [3CR]
- Discrete Mathematics [4 credits] [4CR]
Upper Division Math Courses
- Computational Abstract Algebra [4 credits] [4CR]
- Computational Differential Geometry [4 credits] [4CR]