Duke University · on Coursera

Data Science Math Skills

4.5(20,000) on Coursera·580K enrolled
Beginner 20 hours English University Certificate
Our recommendation
Duke University's short course covering the essential maths for data science — set theory, functions, probability and basic calculus concepts. It is a gentle refresher aimed at filling gaps before a data-science course, not a full maths programme.

Good for: Beginners who want to shore up the basic maths before data science.

Less suitable if: You already have a solid maths background, or you want rigorous depth.

Skills you'll gain

MathematicsProbability basicsSet theoryFunctionsData-science foundations

Is this course right for you?

A good fit if you…

You want a maths refresher for data science
You have gaps to fill
You are new to data

Consider something else if you…

You already have strong maths
You want rigorous depth
You want applied coding

Requirements: School-level maths.

Realistic time: About 20 hours; two to three weeks part-time.

About this course

Data Science Math Skills is Duke's accessible introduction to the mathematical concepts data science builds on — set theory, real line and interval notation, counting and combinatorics, probability rules, Bayes' theorem, and random variables. It's designed for learners who want to start a data science learning path but feel uncertain about their mathematical foundation.

What you'll learn

Apply set theory and interval notation used in data science
Calculate permutations and combinations for probability problems
Apply the rules of probability including conditional probability
Understand and apply Bayes' theorem
Work with random variables and basic probability distributions

This course includes

20h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language

What it costs

Free to audit on Coursera; the certificate needs a subscription (about $49 a month), with financial aid available.

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Is the certificate recognised?

Issued through Coursera with Duke University. The understanding is the value.

Instructor

DE
Daniel Egger / Paul Bendich
Coursera instructor
580K+ learners3 courses4.5 instructor rating

Taught by Daniel Egger and Paul Bendich, Duke University mathematics faculty, designed specifically for learners approaching data science from non-mathematical backgrounds.

About this provider

CO
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Frequently asked questions

Yes as a gentle refresher of the maths behind data science, especially if you have gaps to fill first.
The essentials — set theory, functions, probability and basic calculus concepts — rather than a full maths course.
You can audit it free on Coursera; the certificate needs a subscription, with financial aid available.
Yes, if the maths in ML courses worries you. It is a light preparation rather than a deep one.
About 20 hours over two to three weeks.
Paid
Free to audit, paid certificate
Enroll now