Enroll Now, Start Today - Data Science Academic Credits

Our Distance Calculus courses are designed to be asynchronous - a fancy term for "self-paced" - but it more than just self-paced - it is all about working on your timeline, and going either as slow as you need to, or as fast as your academic skills allow.

Many students need a Calculus course completed on the fast track - because time is critical in finishing calculus courses needed for academic prerequisites and graduate school applications.

Here is a video about earning real academic credits from Distance Calculus @ Roger Williams University:

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