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Learner Reviews & Feedback for Data Science Math Skills by Duke University

4.5
stars
11,647 ratings

About the Course

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!...

Top reviews

AS

Jan 11, 2019

Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)

VS

Sep 22, 2020

This course syllabus is great. It starts wonderfully. Week 1 to 4 is taught by Paul Bendich, and Daniel Egger the instruction is awesome. Effective way to refresh and add the Data Science math skills!

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2126 - 2150 of 2,586 Reviews for Data Science Math Skills

By Gloria P

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Jul 28, 2020

Very engaging instruction and interesting content.

By Kaue C C

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May 9, 2020

Great introductory course for people outside STEM.

By Mohammed M

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May 5, 2020

thx you i have learned alote from this Coutsera...

By Claudia R R

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Apr 17, 2020

Good course. But course material could be improved

By fabio J

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Sep 21, 2019

Great introduction / refresh to math & probability

By Jaime M

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May 16, 2017

Muy buen curso como base para el analisis de datos

By Ali N

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Apr 13, 2020

Overall, the course was good, but I expected more

By Anurag K V

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Feb 2, 2022

It was a good experience...I enjoyed it totally.

By Gilmar N

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May 28, 2020

It lacks some more problem solving explanations.

By SACHIN N P

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May 19, 2020

this course is useful to get the logic of maths.

By James M

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Mar 31, 2018

great introduction and refresher to maths skills

By Myo T H

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May 24, 2020

Probability Course is difficult to understand

By Joshua C

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Aug 29, 2017

The first three chapters are relatively easy.

By John R

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Jul 18, 2022

the probability section was kinda ridiculous

By Subrata M

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Dec 5, 2021

Probability part is not very well explained.

By Odhiambo N

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Nov 25, 2021

It was awesome learning from Duke University

By Muhammad A M

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Jul 1, 2021

The explanation is kind of hard to uderstand

By Ro

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Dec 6, 2020

Long but very informative course to work on!

By Anshul v

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May 30, 2020

interesting and learning more inside course.

By Lei H

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Apr 27, 2020

Good examples and illustration. Good tests.

By Belen R R

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Oct 26, 2019

A veces las explicaciones no son tan claras

By Aditya R S

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Aug 2, 2021

Great course, will give you great insights

By milly

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Aug 20, 2020

Good but need more informative information

By Monish P

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Jun 8, 2020

Good it was perfect for beginners like me.

By Faizia M

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Sep 4, 2020

This is helpful for gaining a knowledge..