# Data Science Mathematics Background

Data Science is a combination of disciplines: 1/2 programmer, 1/2 mathematician/statistician.#### 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]

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

There are no short-cuts in building up your creds as a mathematician for data science. There are TONS of free courses online (some of which are really excellent), but if you plan to formalize your student of Data Science with a degree or certificate, 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.

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:

- 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: Feb 25, 2020*

Review by: Jessica M.

Courses Completed: Applied Calculus

Review: I highly recommend this course. I started the Kennedy School at Harvard with a last-minute admission, but my application required the Liberal Arts calculus course, so I had to finish the course in 3 weeks. Diane was an awesome instructor! The class was surprisingly interesting. If you need to take calculus fast, this is the program to use.

Transferred Credits to: Kennedy School of Government, Harvard University

*Date Posted: Sep 6, 2020*

Review by: Mark L.

Courses Completed: Applied Calculus

Review: Great course. Because of this class I was able to meet the entry requirements for my EMBA program on a tight time window in addition to sharpening math skills from classes taken over 15 years ago!

Transferred Credits to: MIT

*Date Posted: Feb 19, 2020*

Review by: Rebecca Johnson

Courses Completed: Applied Calculus

Review: I took the Business Calculus course from Distance Calculus in 2013. I was admitted to my MBA program, but then they told me I needed to take Calculus before starting the program. I finished the Business Calculus course in about 3 weeks in August before my program started. Not the most fun thing to do over the summer, but at least I got it done. Thanks Diane and Distance Calculus team!

Transferred Credits to: Kellogg MBA Program