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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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1626 - 1650 of 2,586 Reviews for Data Science Math Skills

By Fred A

Oct 1, 2022

By PHILASANDE T N

Apr 22, 2021

By SAGAR M V

Aug 27, 2020

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By Rishabh S

Jun 3, 2020

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By DASARI S R

May 12, 2020

5

By Ranjana P

May 9, 2020

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By Abdelmenem E

Mar 4, 2018

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By Wut H H H

Apr 6, 2017

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By Joseph A V

Aug 14, 2020

Relatively a good refresher course, although coming from Duke U I expected better. There are too many tweaks (lack of scaffolding) that need to be made from a pedagogical standpoint from weeks 3 and 4. Probably need to make it a 5-week course and not try to cram everything into week 4 just to finish the course. Also, the time limit to take the final test was way too short and needed to be set for at least an hour (problems 2 4 11 12 take at least 20 minutes between setting up probability doing calculations and checks). Also, too many glitches with answers coming up in computer code (Over & Over) which basically buries the learner and forces them to guess if they have no clue what the code means, including the anxiety and disorientation it causes during the final. Many times taking quizzes I felt like the problems were made more for a computer programming course than a refresher course. meant to re-sharpen math skills for data science.

By Dejan Đ

Oct 11, 2017

As it is now, the course is a much better resource for reviewing the material (which was fine for me as it was what I was trying to do) than for learning it first time. It would be much better if it had more of the same, which is why I am giving it 4 stars instead of 5. In my opinion, it is too brief; I hope to see a part 2 expanding on the material provided here. Many of the topics mentioned, and they really were mentioned more than really taught, should have been talked about in more detail. I've completed the whole course in about 4-6 hours over 2.5 days. It is a good attempt, but it is hardly a sufficient preparation for the field of Data Science; students looking to take the course should be aware of this.

TLDR: A nice and brief overview of many important concepts (sadly, missing linear algebra) which lay the mathematical foundation for getting into Data Science. Needs to be expanded upon.

By Anantharaman K

Apr 9, 2020

First I would like to thank the instructors, Paul Bendich and Daniel Egger for doing such a wonderful job of creating a power-packed course. I really loved the course. I'm a post graduation pursuer in field of data analytics and I was looking to Brush Up my math Skills as you know data science is a multidisciplinary subject with heavy emphasis on math and stat. The course was neatly done right down from technical aspects to content, the video companion sure provided a lot of help. I would like to mention Paul because his enthusiasm and energy was contagious even though it's a video. The only Con I felt was that Bayesian theorem could've been excellent if it had 2 or 3 more different problems that was solved; Granted, that might make the content a little bit longer than a 4-week course but I felt Sets could be little bit trimmed and Bayesian Theorem little more enhanced.

By Michael R

May 25, 2020

In the end I liked the course. The first part was boringly simple though with a few surprises. The second part was, it seemed to me, absurdly difficult, with the tests requiring a higher degree of skill than implied by the lectures. I think the lectures were theoretically preparation for the test, but in practice were not any where near what would be required for to perform well on the tests. I went to other sources such as Khan academy and the internet to gain the skills I needed to do the tests on the second part. Still, once I had, through other sources, acquired the requisite skills, the lectures made more sense to me and I actually enjoyed them the second time around.

By Francois C

May 14, 2020

The last section was really tough and a bit more explanation or examples related to the last test would have been appreciated. I have a background of statistics/probabilities knowledge, I imagine students going through that course with no prior knowledge might fail to succeed the tests and give up.

For example: the question about the full house is not intuitive at all and does not seem to be explicated in the videos/video companions. I understand it requires the student to search for himself but this one is really hard, and I had to look for a poker lesson on the internet to understand the calculation of this one.

But thank you for this course, it was great to follow.

By Rahulraj S

Apr 5, 2020

The course is intuitive and helps a lot with learning Mathematics (mostly on the statistics and probability side of things) all of which is extremely useful when working on Machine Learning algorithms. But, one major feedback that I would like to give is, the last portion of the lecture with topics:

1 Probability Distribution

2 Bayes Theorem

3 Joint and Conditional Probability

The course should have probably split these topics into separate weeks and elaborated more on these. Just 12 minutes is not enough to understand Bayes Theorem or Joint Probabilities, it becomes difficult and I had to watch many other lectures and tutorials to get a better understanding.

By Jill F

May 4, 2022

This is a useful course to uncover gaps and refine critical skills needed for your data science learning journey. If you've already got pretty good math skills, this will be a nice refresher. If your math skills are a bit rusty or its been a few decades since you worked with permutations and Bayesian reasoning, you'll probably need to access additional resources and spend several hours getting up to speed on concepts to be adequately prepared for the quizzes.

I'm glad I took this course and appreciate the rationale behind it, ... but it took far more time to feel comfortable with key concepts than I expected.

By Karthikeyan R

Jul 5, 2020

First three weeks progresses very quickly and easily with very good explanations and examples. The last week is packed with theory that can be understood only after thorough practice. A good refresher of high school math sprinkled with some advanced concepts.

The teaching was easy to follow. There was a lot of confusion for me when the instructor mixed lowercase and uppercase letters and when there were interruptions in the video for corrections. The quizzes were well framed and comprehensively covered all topics in the videos. Videos dedicated to solving more problems would've been helpful.

By Lisa F

May 9, 2020

This was a great foundational course in data science. It does not assume previous knowledge of anything it covers, which was helpful for me because I haven't seen any of these topics since high school (about 10 years ago). I have always struggled to understand probability, and it was no different in this course (probability was my least favorite unit) but I appreciated the practice anyway. Highly recommend for anyone interested in dipping a toe into data science. It's a great intro and helped me realize that I probably would rather stick to data analytics instead!

By David N

May 17, 2020

This course was enjoyable, but a little too basic for my taste. All modules, except for the last were a breeze to go though. The last module was finally something which took me a while to complete. But this is probably not the courses fault, I should have read the syllabus more closely. The instructors are nice and knowledgeable. I would recommend this course only to students that are at the very beginning of their journey into data science and really need a refresher on some core mathematical topics.

By Isaac M

Jan 14, 2018

This course was very challenging for me (I'm a musician). I wanted to review the concepts presented in this course to get back on track with my math skills. It was fun, but required me so much time to understand what is what and how to apply it to problem solving. Take this course if you are into Data Science or if you are a programmer who wants to plot data for any given purposes. If you are a musician, well... It will refresh your memory and maybe it will also have an impact on your music : p

By Bud B

Apr 16, 2023

This was a fantastic program and extremely informative for someone just starting out in the field. Everything was explained very well and the examples were very helpful prior to taking the exams at the end. However, the last 2 modules were very sparse and did not accurately cover the material. The discussion forums are a great resource for additional material and I was able to piece it together with some help from the internet. Overall a great course and will recommend it to my colleagues.

By A. G

Feb 14, 2022

It was good in general, but in the final week it would have been more helpful to have seen a video where they teach you to comprehend math sentences associated to probabilities. One thine is the basic formulas, but you can complicate a sentence with key information as much as possible and since the math behind Bayes Theorem isn't complicated, it's all in the reading comprehension. So I would complement week 4 with a video on how to read questions asociated with Bayes Theorem.

By Thuy N

Oct 22, 2020

Pros: Very good way to refresh your math skills; The instructors provide notes in PDF so you can quickly review the content before and after the lecture; Instructions were clear and easy to follow; Relevant quizzes

Cons: I don't think this is enough math for data science, so the name may be misleading. I would really love it if they follow up with a sequel course with more advance content

Overall: Good for someone who hasn't touched math for a while to refresh knowledge

By Vitor M A A

May 2, 2023

I started the course with no bases. It had a logical sequence and the instructors were really talented and did a good job. Unfortunately, I feel like in the last 2 weeks we jumped from simple things to really hard really quick which confused me and made me look for other instructors on youtube. so I was able to pass the last 2 tests.

But like i said, I think the course was really good and I'm grateful for the instructors for putting out such an important course!

By Mayamma J

Apr 30, 2020

This course is a good introduction of basic Mathematics and Statistics not only for Data Science students, but also for anyone wishing to pursue a course that require knowledge of basic Math/Statistics. Those without any background in Math/Statistics need to practice more sums to master the concepts. In this regard, providing additional resources would be very helpful. A big thank you to the instructors for designing and offering this course through Coursera!

By Bruno d P K

Sep 11, 2020

Wish we had more time for the content of week 4, I thought it was harder and had more content squeezed in. For the past topics, I did a bit of review with some content from Khan Academy as I found it easier to understand from their videos. Then watching the videos here again, it became much clearer. There were some exercises that were repetitive too. Lots of useful tips too, and some exercises to help you fixate or understand the course content. Thank you!