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Data Science Math Skills, Duke University

1,445 个评分
334 个审阅


Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material. Topics include: ~Set theory, including Venn diagrams ~Properties of the real number line ~Interval notation and algebra with inequalities ~Uses for summation and Sigma notation ~Math on the Cartesian (x,y) plane, slope and distance formulas ~Graphing and describing functions and their inverses on the x-y plane, ~The concept of instantaneous rate of change and tangent lines to a curve ~Exponents, logarithms, and the natural log function. ~Probability theory, including Bayes’ theorem. While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." Good luck and we hope you enjoy the course!...


创建者 PS

Jul 23, 2017

This is neat little course to revise math fundamentals. I generally find learning probability a little tricky. This course helped me a lot in better understanding Bayes Theorem. Thank you professors.

创建者 MG

Mar 28, 2018

Please include integration, algorithm analysis (big O, theta, omega), recursion and induction. Your course is helpful, thank you. If you add those things I've mentioned it would be absolute gold.


326 个审阅

创建者 Michael Meighu

Dec 14, 2018

amazing! i love this course

创建者 Mukund Bhagwan Gwalani

Dec 04, 2018

Very good informative, surely has helped me understand probability more intutively.

创建者 Vivien Pichon

Nov 28, 2018

Great course to be back on tracks with mathematics and probability.

创建者 Matthew Watts

Nov 15, 2018

nice course, thanks!

创建者 Joy Ghosh

Nov 13, 2018

This course from course era has given me new opportunity to explore and has given me confidence in data science ,

创建者 Lucia Sagatova

Nov 12, 2018

The course started nice and well explained, there are some useful info missing, e.g. what is Euler's constant and why is it defined as it is and then more practice examples would be also welcome. All that would be fine and I would have given the course full 5 stars, but I felt really discouraged with so many errors in the practice quizes and even in the last graded quiz. Additionally, it was a bit annoying that I could not finish the quiz on my phone as in one of the questions there was only the problem and the possible answers visible, not the question itself.

创建者 Valerii Marchenkov

Nov 11, 2018

Great course!

创建者 GJ

Nov 10, 2018

I leaned a lot especially in probability. But I had to search around various other resources before I got the hang of Bayes theorem. Also a tree diagram approach to both conditional and Bayes theorem will help get to the understanding faster.

创建者 LI MengAi

Nov 09, 2018

good class

创建者 Hein Zin

Nov 06, 2018

Nice start math for Data Science