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.

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

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!

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!

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!

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.

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.

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.

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.

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.

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

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

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.

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.

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!

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.

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.

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.

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.

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.

Coverage of Content is good. Section 1, 2 and 3 - was very good. But Section 4 and 5 the content is not easily understood. It will be difficult for students to grasp all these concepts. Suggest - More detailed explanations and more hands on practice in each of the submodules of the Module 4 and 5.

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

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.

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.

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.