Chevron Left
Back to Data Science Math Skills

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!

Filter by:

1651 - 1675 of 2,586 Reviews for Data Science Math Skills

By Hamid H

May 21, 2023

I completed the Data Science Math course on Coursera, and it was truly exceptional! The course covered a wide range of mathematical concepts essential for data science, and the instructors explained them clearly with practical examples. The interactive learning environment and flexibility of Coursera made it easy to fit into my schedule. I highly recommend this course to anyone looking to strengthen their mathematical foundation for data science.

By Jurijs S

Jan 17, 2024

A good course, especially for people who want to get started in this field! All initial, mathematical concepts and principles are explained step by step. The language of the lectures is accessible. Very well prepared materials (Video companions). The last two topics on probability will require some effort, but it is doable and worth it. Overall a very positive impression. Many thanks to the lecturers for their knowledge and good work.

By Adam S

Apr 26, 2022

Good course overall. There appeared to be some bugs in the course for me - not sure if that is something widespread on Coursera or specific to this course, but for example, with some of the tests the correct answer to some questions were visually different. For example the correct answer might be bold, or a different font. Very odd. I also am pretty sure that for at least a couple of the questions the answers given are not correct.

By Emmanuel M

Jun 19, 2020

A good and very concise course that goes through the many mathematical tools used in Data Science : Set Theory, Functions, Rate of Growth, and Probability. The material is short and to the point, the test rather easy, apart from the last module, taught by Daniel Eggers, which is quite hard in comparison. It is doable though, just go over it a few times, all you need is there. I had this course for free. Thanks for the opportunity.

By Evan P

Jan 17, 2021

This is a great course for refreshing yourself with topics in probability and statistics. The quizzes are great too because they really allow you to challenge yourself. I also appreciate the video companion notes, because if there is something during the discussion that you would like to focus back on, it allows you to take a step back and review the notes. Grateful to the team at Duke University for offering this helpful course.

By hilton m

May 13, 2020

coming into this with a large gap in time between math classes i was a little confused on how to enter the equations into my calculator which i think would help a bit more . however as i said if i had taken at least 2 math classes before this i probably wouldnt find it that hard hahaha. otherwise great intro and it did teach me a lot and hopefully when i get into more math classes all this can click easier .

highly recommend

By Georgios D

Aug 8, 2020

Week 1 and Week 2 are really easy. When the tutor changed in Week 3 things started to become more difficult but still the passing grade was achievable. The problem came with Week 4. Understanding the lectures was easy but completing the tests was quite challenging and needed a lot of studying to complete them. The videos of Week 4 look easy and understandable but the test is way more difficult and in depth than the lectures

By Solaiman H

Jul 13, 2020

This course helped me to horn my basic math related to Data Science. Most of them were familiar to me but it was really fun to revise them more effectively this time. I loved the real-world example of many topics and will suggest using more real-world examples with calculation. If are a beginner at Data Science and you want to reshape your math skill I will recomend this course to you. Thank You.

By Alexander D K

Aug 3, 2019

Very useful indeed. The ressources have a good format but could be more grouped. The videos have good content but should be a bit more curated as they contain quite a few small but confusing errors. The task are very well selected but do not cover every topic to the same amount. I would also wish for a finals test that integrates many of the newly acquired skills, rather than have them isolated.

By Nishant (

Mar 5, 2022

I enjoyed the 4th week and felt it to be the most challenging, however having some prior knowledge on the topic is helpful as the practice quizzes can ramp up in difficulty quite quickly although the challenge is enjoyable. The course progresses quickly however some may find the earlier modules easier and may consider skipping to the practice tests. Overall, the course was good!

By Diana S

Aug 14, 2023

The section on Probability/Bayes' Theorem could use more examples of how numbers in the formulas are derived. It seemed a bit fast-paced for someone who has not seen statistics and probability in ten years. This was meant as a refresher but it really slowed me down to have to stop the videos often and try to figure out where the numbers they were writing were coming from.

By Colin P

Mar 28, 2018

Good refresher course on introductory math concepts relevant to data science (I hope!). The probability modules were a little light for me, given how deep probability is. I think more time/instruction could of been spent on this subject. Overall, this is a good course if you want a refresh on math concepts, or to firm up some learning gaps before taking more math courses.

By Farshid A

Jun 15, 2020

In overall this was a great math course, Dr Bendich is a great professor and he teaches concepts very clearly however I had a hard time to understand really what Dr Egger is trying to teach it was more like reviewing concepts for himself rather than explaining things. I had to take some complementary courses in udemy in order to understand what he was trying to teach.

By Charissa B

Sep 30, 2020

It's a refresher of sorts for long forgotten high school algebra, calculus, and probabilities. It's helpful for reminding you of the concepts and have a vague general sense of how they are processed. The video companion PDF have been helpful, though I would personally appreciate a few more examples just to help me really understand how the computations take place.

By Stylianos I

May 8, 2020

I really enjoyed the course. It is true that in the beginning the knowledge that was given was very basic. I would like to have more practice quizzes than the course has acquired. I put a 4-star rating having in mind that 5-star ratings are for exceptional cases. The course is fairly good for an introduction to the data science and so I definitely recommend it.

By Kaung K K

Apr 21, 2020

This course makes me realize which part of my math skills was lacking and learnt a lot of techniques from here , although if you were finding a basic one this is not for u coz probability part is not that fundamental and they just covers the contents in a little rough way, hope they made it a little better, its just a little ya know, .... Great course really

By Katya K

Nov 11, 2019

the first few lectures, first half is really easy to follow, quizzes are a great way of firming up the new knowledge. Last few lectures are very challenging comparing to the beginning of the course, and I felt that some have missed key steps unexplained. The final quiz doesn't provide feedback which makes it useless as a way to recapitulate and practice.

By Ashray M

Mar 30, 2017

Refreshing your Basics

The whole course is a just brushing up your basic math. The videos are brief and to the point, and problems make you use your brains and they are not right out of the video or any other reading material. I feel only Bayes and binomial theorem videos are not comprehensive and the problems a quite challenging.

By 肖霁航

Sep 18, 2019

All skills taught in this course are prileminary are preliminary and essentially. In my pont of view, anyone who get familiar with probabilitis and statistics in high shcool chould pass this course easily. Though its content is easy, it's still a good course that anyone can review key points and take some practices in class.

By Maria A E

Jul 13, 2020

The first parts were easy but I have difficulty grasping the concepts in Bayes theorem and binomial theorem yet. I think it needs more content and more sample exercises. It could also help to put exercises in between videos for the concept to stick. All in all, the course was very informative and I learned a lot. Thank you!

By Philippe G

Nov 14, 2020

Overall, good mix of reviewing introductory 1st year university math with some new concepts for myself. Perhaps some of the Week 1 content was a bit too introductory. On the flip side, Week 4 quizzes on Bayes and probability were a nice challenge!

Perhaps some introductory Linear Algebra would have been nice to include too.

By Alexandra K

May 27, 2020

Overall it was really good and I remembered a lot of things that I had forgotten. I won't lie - I had a really hard time at module 4 and had to watch more videos on its topics. It was my first time learning specifically about the topics in module 4, so I believe that this is one of the reasons that I found it so difficult.

By Wan A

Apr 12, 2020

This course is a great place for those who want to get started learning and also a good refresher for those who have learned Calculus, Discrete Math, and Linear Algebra. Overall the course content is easy to understand except for the Week 4 module. I feel like more example should be given for the problem solving question.

By V R

Apr 22, 2020

Overall, a great course. Can get a little too basic at times. But, very good for any beginners or intermediate level student/professionals who want to get into Data Science and need a little bit of Math background for it. It is a great "first course" for anyone opting for Data Science or Machine Learning course path.

By Ana B

Jun 5, 2020

A good course if you are in need of refreshing your math skills. While the lectures are mostly easy to understand, the questions are often significantly more difficult than the examples given during lectures. That said, it does cover a fair amount of topics that are important for advancing a career in data science.