About this Course
162,290 recent viewsData 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.
Learner Career Outcomes
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got a tangible career benefit from this courseFlexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
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Beginner LevelApprox. 13 hours to completeEnglish
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
Skills you will gain
- Bayes' Theorem
- Bayesian Probability
- Probability
- Probability Theory
Learner Career Outcomes
12%
got a tangible career benefit from this courseFlexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner LevelApprox. 13 hours to completeEnglish
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
Instructors
Daniel Egger
Executive in Residence and Director, Center for Quantitative ModelingPratt School of Engineering, Duke University 936,835 Learners 8 CoursesPaul Bendich
Assistant research professor of Mathematics; Associate Director for Curricular Engagement at the Information Initiative at DukeMathematics 308,721 Learners 2 CoursesOffered by

Duke University
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Syllabus - What you will learn from this course
Week 1
18 minutes to complete
Welcome to Data Science Math Skills
This short module includes an overview of the course's structure, working process, and information about course certificates, quizzes, video lectures, and other important course details. Make sure to read it right away and refer back to it whenever needed
18 minutes to complete
1 video (Total 3 min), 2 readings
1 videoWelcome to Data Science Math Skills2m
2 readingsCourse Information5m
Weekly feedback surveys10m
4 hours to complete
Building Blocks for Problem Solving
This module contains three lessons that are build to basic math vocabulary. The first lesson, "Sets and What They’re Good For," walks you through the basic notions of set theory, including unions, intersections, and cardinality. It also gives a real-world application to medical testing. The second lesson, "The Infinite World of Real Numbers," explains notation we use to discuss intervals on the real number line. The module concludes with the third lesson, "That Jagged S Symbol," where you will learn how to compactly express a long series of additions and use this skill to define statistical quantities like mean and variance.
4 hours to complete
10 videos (Total 93 min), 4 readings, 4 quizzes
10 videosSets - Basics and Vocabulary9m
Sets - Medical Testing Example11m
Sets - Venn Diagrams7m
Numbers - The Real Number Line9m
Numbers - Less-than and Greater-than6m
Numbers - Algebra With Inequalities10m
Numbers - Intervals and Interval Notation7m
Sigma Notation - Introduction to Summation9m
Sigma Notation - Simplification Rules7m
Sigma Notation - Mean and Variance12m
4 readingsA note about the video lectures in this lesson3m
A note about the video lectures in this lesson10m
A note about the video lectures in this lesson10m
Feedback10m
4 practice exercisesPractice quiz on Sets15m
Practice quiz on the Number Line, including Inequalities25m
Practice quiz on Simplification Rules and Sigma Notation20m
Graded quiz on Sets, Number Line, Inequalities, Simplification, and Sigma Notation35m
Week 2
3 hours to complete
Functions and Graphs
This module builds vocabulary for graphing functions in the plane. In the first lesson, "Descartes Was Really Smart," you will get to know the Cartesian Plane, measure distance in it, and find the equations of lines. The second lesson introduces the idea of a function as an input-output machine, shows you how to graph functions in the Cartesian Plane, and goes over important vocabulary.
3 hours to complete
8 videos (Total 72 min), 3 readings, 3 quizzes
8 videosCartesian Plane - Plotting Points7m
Cartesian Plane - Distance Formula10m
Cartesian Plane - Point-Slope Formula for Lines8m
Cartesian Plane: Slope-Intercept Formula for Lines7m
Functions - Mapping from Sets to Sets7m
Functions - Graphing in the Cartesian Plane11m
Functions - Increasing and Decreasing Functions10m
Functions - Composition and Inverse10m
3 readingsA note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
Feedback10m
3 practice exercisesPractice quiz on the Cartesian Plane15m
Practice quiz on Types of Functions20m
Graded quiz on Cartesian Plane and Types of Function40m
Week 3
3 hours to complete
Measuring Rates of Change
This module begins a very gentle introduction to the calculus concept of the derivative. The first lesson, "This is About the Derivative Stuff," will give basic definitions, work a few examples, and show you how to apply these concepts to the real-world problem of optimization. We then turn to exponents and logarithms, and explain the rules and notation for these math tools. Finally we learn about the rate of change of continuous growth, and the special constant known as “e” that captures this concept in a single number—near 2.718.
3 hours to complete
7 videos (Total 66 min), 3 readings, 3 quizzes
7 videosTangent Lines - Slope of a Graph at a Point10m
Tangent Lines - The Derivative Function9m
Using Integer Exponents7m
Simplification Rules for Algebra using Exponents11m
How Logarithms and Exponents are Related12m
The Change of Base Formula4m
The Rate of Growth of Continuous Processes11m
3 readingsA note about the video lectures in this lesson10m
A note about the video lectures in this lesson3m
Feedback10m
3 practice exercisesPractice quiz onTangent Lines to Functions10m
Practice quiz on Exponents and Logarithms40m
Graded quiz on Tangent Lines to Functions, Exponents and Logarithms45m
Week 4
3 hours to complete
Introduction to Probability Theory
This module introduces the vocabulary and notation of probability theory – mathematics for the study of outcomes that are uncertain but have predictable rates of occurrence.
3 hours to complete
8 videos (Total 66 min), 4 readings, 4 quizzes
8 videosProbability Definitions and Notation7m
Joint Probabilities6m
Permutations and Combinations12m
Using Factorial and “M choose N”6m
The Sum Rule, Conditional Probability, and the Product Rule8m
Bayes’ Theorem (Part 1)10m
Bayes’ Theorem (Part 2)5m
The Binomial Theorem and Bayes Theorem8m
4 readingsA note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
Feedback10m
4 practice exercisesPractice quiz on Probability Concepts25m
Practice quiz on Problem Solving25m
Practice quiz on Bayes Theorem and the Binomial Theorem25m
Probability (basic and Intermediate) Graded Quiz50m