Data Science Fast for Academic Credits
Unable to "wait for the next academic semester" to complete a Data Science course? Distance Calculus @ Roger Williams University has you covered!
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]
Distance Calculus is designed to get you enrolled in Data Science immediately, and to have you finish the course as quickly as your academic skills allow.
Each Calculus course is different, some are more difficult and longer than others. But depending upon which Distance Calculus course, you could finish your course in a matter of weeks. It all depends upon your academic skills - some students are able to go lightning fast through the courses, some students need more time. Our only rule is that you go through the courses CORRECTLY and learn the material in our mastery learning format at 100% completion.
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 Data Science 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
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 Online Course FAST
- Data Science Online Course For Credit Start Immediately
- Data Science Online Course For Credit Start Today, Finish Quickly
- Data Science Accredited Online Course
- Data Science Summer 2024 Online Course
- Data Science Winter 2024 Online Course
- Data Science Summer Course
- Data Science Winter Course
- Data Science Spring Course
- Data Science Fall 2024 Online Course
Distance Calculus - Student Reviews
Date Posted: Apr 13, 2020
Review by: Jorgen M.
Courses Completed: Calculus I
Review: I really enjoyed this course, much more than I thought I would. I needed to finish this course very fast before starting my graduate degree program @ Kellogg. I was able to finish in 3 weeks. I liked the video lectures and the homework process. I highly recommend this course.
Transferred Credits to: Kellogg School of Business, Northwestern Univ
Date Posted: Dec 8, 2020
Review by: Aileen C.
Courses Completed: Differential Equations
Review: This course may be more difficult than your average differential equations course, which better prepares you to use these skills in your degree. The self-learning does make learning some of the concepts challenging, but you get the help you need to understand these concepts.
Transferred Credits to: Johns Hopkins University
Date Posted: Jan 8, 2021
Review by: Cristian Mojica
Student Email: comojica@ucdavis.edu
Courses Completed: Probability Theory
Review: A fantastic course! I was able to complete it in about half a year (with a few gaps) alongside other coursework I was completing. There are no deadlines except the one-year mark after registering, so you work at your own rate and schedule. Probability Theory is required for me to apply to Master's programs in Statistics, so I was glad when I found Distance Calculus. While the course was slightly less difficult than I originally expected, there were parts that definitely slowed me down and made me think. (Also, although calculus is not everywhere in the course, it is everywhere in normal and exponential variables and beyond, so make sure to review derivatives and integrals (single and double)!) I used Mathematica for my software, and it helped speed along calculations and proved to be the perfect stage and tool for this material. I think visual learners will absolutely revel in how the material is presented in this course. (I know I did!) As there is plenty of writing and calculation to do, you have many opportunities to develop and strengthen your voice as a mathematician. The modern format of 80% electronic notebook work and 20% handwritten work is an excellent mixture for studying probability theory and grasping its core ideas. Dr. Curtis is clear in his answers to any questions and concerns you may have and is highly responsive to email and chat, and to responses you leave in your notebooks. He truly wants to help you and to see you succeed, and he is always on your side. I highly recommend Probability Theory with 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]