Data Science Math Skills

Duke University

Acerca de este Curso

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!

Curso 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Nivel principiante

Aprox. 14 horas para completar

Sugerido: Four weeks, 3-5 hours per week.

English

Subtítulos: English

Habilidades que obtendrás

StatisticsBayesianData ScienceGraph Of A Function

Curso 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Nivel principiante

Aprox. 14 horas para completar

Sugerido: Four weeks, 3-5 hours per week.

English

Subtítulos: English

Syllabus - What you will learn from this course

1

Section

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...

1 video (Total 3 min), 2 readings

1 videos

Welcome to Data Science Math Skills2m

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....

10 videos (Total 93 min), 4 readings, 4 quizzes

10 videos

Sets - 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 readings

A note about the video lectures in this lesson3m

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

2

Section

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....

8 videos (Total 72 min), 3 readings, 3 quizzes

8 videos

Cartesian 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 readings

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

3

Section

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....

7 videos (Total 66 min), 3 readings, 3 quizzes

7 videos

Tangent 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 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

4

Section

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....

8 videos (Total 66 min), 4 readings, 4 quizzes

8 videos

Probability 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 readings

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

Instructors

Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling

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

When will I have access to the lectures and assignments?
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.
What will I get if I pay for this course?
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.
What is the refund policy?
Is financial aid available?
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.
Will I receive a transcript from Duke University for completing this course?
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

Data Science Math Skills