Informações sobre o curso
4.5
1,348 ratings
314 reviews
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!...
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Beginner Level

Nível iniciante

Clock

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

Aprox. 14 horas restantes
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English

Legendas: English

Habilidades que você terá

Bayes' TheoremBayesian ProbabilityProbabilityProbability Theory
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Beginner Level

Nível iniciante

Clock

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

Aprox. 14 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
18 minutos para concluir

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 vídeo (Total de 3 min), 2 leituras
Reading2 leituras
Course Information5min
Weekly feedback surveys10min
Clock
4 horas para concluir

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 vídeos (Total de 93 min), 4 leituras, 4 testes
Video10 videos
Sets - Medical Testing Example11min
Sets - Venn Diagrams7min
Numbers - The Real Number Line9min
Numbers - Less-than and Greater-than6min
Numbers - Algebra With Inequalities10min
Numbers - Intervals and Interval Notation7min
Sigma Notation - Introduction to Summation9min
Sigma Notation - Simplification Rules7min
Sigma Notation - Mean and Variance12min
Reading4 leituras
A note about the video lectures in this lesson3min
A note about the video lectures in this lesson10min
A note about the video lectures in this lesson10min
Feedback10min
Quiz4 exercícios práticos
Practice quiz on Sets15min
Practice quiz on the Number Line, including Inequalities25min
Practice quiz on Simplification Rules and Sigma Notation20min
Graded quiz on Sets, Number Line, Inequalities, Simplification, and Sigma Notation35min

2

Seção
Clock
3 horas para concluir

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 vídeos (Total de 72 min), 3 leituras, 3 testes
Video8 videos
Cartesian Plane - Distance Formula10min
Cartesian Plane - Point-Slope Formula for Lines8min
Cartesian Plane: Slope-Intercept Formula for Lines7min
Functions - Mapping from Sets to Sets7min
Functions - Graphing in the Cartesian Plane11min
Functions - Increasing and Decreasing Functions10min
Functions - Composition and Inverse10min
Reading3 leituras
A note about the video lectures in this lesson3min
A note about the video lectures in this lesson3min
Feedback10min
Quiz3 exercícios práticos
Practice quiz on the Cartesian Plane15min
Practice quiz on Types of Functions20min
Graded quiz on Cartesian Plane and Types of Function40min

3

Seção
Clock
3 horas para concluir

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 vídeos (Total de 66 min), 3 leituras, 3 testes
Video7 videos
Tangent Lines - The Derivative Function9min
Using Integer Exponents7min
Simplification Rules for Algebra using Exponents11min
How Logarithms and Exponents are Related12min
The Change of Base Formula4min
The Rate of Growth of Continuous Processes11min
Reading3 leituras
A note about the video lectures in this lesson10min
A note about the video lectures in this lesson3min
Feedback10min
Quiz3 exercícios práticos
Practice quiz onTangent Lines to Functions10min
Practice quiz on Exponents and Logarithms40min
Graded quiz on Tangent Lines to Functions, Exponents and Logarithms45min

4

Seção
Clock
3 horas para concluir

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 vídeos (Total de 66 min), 4 leituras, 4 testes
Video8 videos
Joint Probabilities6min
Permutations and Combinations12min
Using Factorial and “M choose N”6min
The Sum Rule, Conditional Probability, and the Product Rule8min
Bayes’ Theorem (Part 1)10min
Bayes’ Theorem (Part 2)5min
The Binomial Theorem and Bayes Theorem8min
Reading4 leituras
A note about the video lectures in this lesson3min
A note about the video lectures in this lesson3min
A note about the video lectures in this lesson3min
Feedback10min
Quiz4 exercícios práticos
Practice quiz on Probability Concepts25min
Practice quiz on Problem Solving25min
Practice quiz on Bayes Theorem and the Binomial Theorem25min
Probability (basic and Intermediate) Graded Quiz50min
4.5
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Briefcase

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Melhores avaliações

por 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.

por 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.

Instrutores

Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling
Pratt School of Engineering, Duke University

Paul Bendich

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

Sobre 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....

Perguntas Frequentes – FAQ

  • 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.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • 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.

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