## 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

## 12%

got a tangible career benefit from this course#### Flexible 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 complete#### English

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 course#### Flexible 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 complete#### English

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**Courses

### Paul Bendich

Assistant research professor of Mathematics; Associate Director for Curricular Engagement at the Information Initiative at DukeMathematics**308,721**Learners**2**Courses## Offered 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 video**

**Welcome to Data Science Math Skills**2m

**2 readings**

Course 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 videos**

**Sets - Basics and Vocabulary**9m

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 readings**

A 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 exercises**

Practice 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 videos**

**Cartesian Plane - Plotting Points**7m

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 readings**

A note about the video lectures in this lesson3m

A note about the video lectures in this lesson3m

Feedback10m

**3 practice exercises**

Practice 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 videos**

**Tangent Lines - Slope of a Graph at a Point**10m

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 readings**

A note about the video lectures in this lesson10m

A note about the video lectures in this lesson3m

Feedback10m

**3 practice exercises**

Practice 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 videos**

**Probability Definitions and Notation**7m

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 readings**

A 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 exercises**

Practice quiz on Probability Concepts25m

Practice quiz on Problem Solving25m

Practice quiz on Bayes Theorem and the Binomial Theorem25m

Probability (basic and Intermediate) Graded Quiz50m