课程信息
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!
Globe

100% 在线课程

立即开始,按照自己的计划学习。
Beginner Level

初级

Clock

Approx. 14 hours to complete

建议:Four weeks, 3-5 hours per week.
Comment Dots

English

字幕:English

您将获得的技能

StatisticsBayesianData ScienceGraph Of A Function
Globe

100% 在线课程

立即开始,按照自己的计划学习。
Beginner Level

初级

Clock

Approx. 14 hours to complete

建议:Four weeks, 3-5 hours per week.
Comment Dots

English

字幕:English

Syllabus - What you will learn from this course

1

Section
Clock
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...
Reading
1 video (Total 3 min), 2 readings
Reading2 readings
Course Information5m
Weekly feedback surveys10m
Clock
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....
Reading
10 videos (Total 93 min), 4 readings, 4 quizzes
Video10 videos
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
Reading4 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
Quiz4 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

2

Section
Clock
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....
Reading
8 videos (Total 72 min), 3 readings, 3 quizzes
Video8 videos
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
Reading3 readings
A note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
Feedback10m
Quiz3 practice exercises
Practice quiz on the Cartesian Plane15m
Practice quiz on Types of Functions20m
Graded quiz on Cartesian Plane and Types of Function40m

3

Section
Clock
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....
Reading
7 videos (Total 66 min), 3 readings, 3 quizzes
Video7 videos
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
Reading3 readings
A note about the video lectures in this lesson10m
A note about the video lectures in this lesson3m
Feedback10m
Quiz3 practice exercises
Practice quiz onTangent Lines to Functions10m
Practice quiz on Exponents and Logarithms40m
Graded quiz on Tangent Lines to Functions, Exponents and Logarithms45m

4

Section
Clock
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. We start with the basic definitions and rules of probability, including the probability of two or more events both occurring, the sum rule and the product rule, and then proceed to Bayes’ Theorem and how it is used in practical problems....
Reading
8 videos (Total 66 min), 4 readings, 4 quizzes
Video8 videos
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
Reading4 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
Quiz4 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
4.5
Direction Signs

38%

started a new career after completing these courses
Briefcase

83%

got a tangible career benefit from this course

Top Reviews

By PSJul 23rd 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.

By MGMar 28th 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.

Instructors

Avatar

Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling
Avatar

Paul Bendich

Assistant research professor of Mathematics; Associate Director for Curricular Engagement at the Information Initiative at Duke

About 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....

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • If you pay for this course, you will have access to all of the features and content you need to earn a Course Certificate. If you complete the course successfully, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. Note that the Course Certificate does not represent official academic credit from the partner institution offering the course.

  • Yes! Coursera provides financial aid to learners who would like to complete a course but cannot afford the course fee. To apply for aid, select "Learn more and apply" in the Financial Aid section below the "Enroll" button. You'll be prompted to complete a simple application; no other paperwork is required.

  • No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

More questions? Visit the Learner Help Center