well the initial part of the course is very basic .. too basic.. the course doesn't scale up with the first 3 weeks. but the instructor is clear and makes concept easy to understand. but things change in the fourth week. the course shifts gears from very easy to intermediate. without much guidance.. or examples

math skills are to be practiced i hope the instructors level out the difficulty level in the course. An ideal math course should have many examples to practice with constant involvement of the instructors , support guys.

just 5 or 10 problems doesn't get you much and when asked to pass with 80% is tough.

. i left the course in week 4 and again completed after i understood week 4 content better.

this course doesn't have many many of the math skills required for data science.

ideally a math course should scale up from simple easy to intermediate to hard and later challenging questions and final assignment should have a combination of first 3 and passing of 70 to 75..

so the course requires

a. more examples for practice with solutions atleast 20 -25 both solved and unsolved

b. more math topics to make it more comprehensive for data science

c. more involvement overall

I definitely learned a lot in this course, and, as someone who has historically avoided mathematics, I think it is a fairly good introduction to these concepts for people at my level. However, I think the course was somewhat inconsistent. The final module could really use some more explanation and examples. Probability is a very abstract field, and it can be difficult to take real world examples and translate them into formulas. I think that the module would benefit greatly from spending some extra time on translating english-language situations into formulas. There were also some non-trivial errors in the videos that need to be corrected. Overall, I'm pretty happy with the course but I think it doesn't yet fill out its potential.

The first two weeks of the course were well explained. But when it came to the probability, the course was confusing so that I had to search for more sources and learn from YouTube. I have been away from math for a long time, so I took this course which is described as for the beginners. I was extremely confused and disappointed about myself for not understanding the concept of Bayes Theorem for example. But when I checked other sources on YouTube, I could understand it easily and only then I was able to answer the quiz questions. So many basic concepts such as Tree diagram which are extremely helpful for grasping the theories and using them in real life situations were not even mentioned.

Pretty good, overall the explanations are clear and the exercises/practice quizzes are really useful to understand the material.

Negative points: the last part on Bayes' Rule and the Binomial Theorem is a bit too fast, and I needed to supplement it by external material to fully understand it. And it would have been great to have a part about linear algebra and maybe calculus, but I guess there were some time and financial constraints that did not allow that.

I still recommend this course, that's a really good refresher or intro. You'll need to supplement it by other material, though.

The positives first: Brought me up to speed on important statistics and probability information for my future career.

The not so good: The second instructor does not need to show his face. That was very distracting.

There was no working often provided in the course notes. Sometimes when I would work through a problem I would make one calculation error and couldn't easily figure out which one it was. I would prefer if they would show each calculation step by step. That would have made things a LOT faster and easier. Instead I relied to brainly, which is a great website.

I think the first two weeks were great but the probability explanations could be better. I'm sure Edgar is a great scientist but he's not very organized and the videos are very cluttered (not everyone is fit to teach just because they are in the industry). The topics covered in the probability portion of this course are better explained on free sites like Khan. I took this course to have a better understanding of the binary classification portion of the referenced specialization but don't think I gained a good understanding of the material from this course alone.

The course started nice and well explained, there are some useful info missing, e.g. what is Euler's constant and why is it defined as it is and then more practice examples would be also welcome. All that would be fine and I would have given the course full 5 stars, but I felt really discouraged with so many errors in the practice quizes and even in the last graded quiz. Additionally, it was a bit annoying that I could not finish the quiz on my phone as in one of the questions there was only the problem and the possible answers visible, not the question itself.

If you are familiar with the concepts in this course, it will be fine. If, however, you happen to discover them for the first time here, the instructors go so quickly in their explanations that you'll end up with a high level of frustration.

When it comes to statistics, fewer concepts introduced per video, and more examples of each concepts would have been a better approach for real beginners.

Finally, don't believe you've acquired the "math skills" necessary for data science just by following this course. In this, the title can be seriously misleading.

The first Half of this course is wonderful. Well presented, interesting and something to look forward to. The second half is done by a different teacher, is confusing, disorganized and and time would be better spent elsewhere. I highly recommend the first half though, and then looking at the topics list for the second half and go elsewhere for those. There are some great recommendations of others videos and courses to cover the 2nd halves content in the course forum as it appears it was a common issue among students.

About half of the concepts in the course were new, half a review of topics I studied in high school, about 15 years ago. For the review topics, this was a good refresher and the concepts came back quickly. For the topics I hadn't studied before, I felt like there wasn't enough explanation to fully understand the topics, and I had to seek out additional explanation outside the course. There could be more opportunities to practice and reinforce the concepts discussed in the lectures before moving onto the quizzes.

Week 1 & 2 were done well. Week 3 & 4 lacked clear explanations. Too often the instructor jumped to the result without showing the work of how he reached the answer. I had to spend a lot of time looking elsewhere for explanations. The quizzes also asked questions on topics not covered in the coursework. For example, the course covered the probability of exactly x out n coin flips. The quiz asks the probability of at least x out n coin flips but the course work does not tell you how to calculate that anywhere.

The last portion is out of reach for the beginner 's level. but the first portion or i must say , 95% of the course is very good for a beginner to learn about hard topics. without the last portion of probability, i must the this could have been complete tutorial. the last portion is out or reach and no way its for beginner and even it seems the teacher didn't give any effort to teach beginner level students. he just tough what he teaches in his normal class to masters or phd level students/

This course was a good refresher to some important math concepts needed for further study of statistics and data science. Most of the modules and videos were clear and easy to follow. However, I found the module on probability to be confusing and overly complex in its structure and explanations. For those with stronger math skills than me, it's probably a fairly easy course. I found it appropriately challenging, and for the most part it built my confidence in this important area.

This course moves very quickly and you will need a scientific Calculator. I was never the best in math, and this gave me a solid view point of the maths I will need to learn better to focus on data science. If you are good with Maths, this might be a great refresher. I worked with a Tutor and got through it, But week 3 I think the videos are out of order, or could be ordered differently. Anyway, I was very challenged and now know exactly where to apply my energy.

The course should be a guide text with very detail readings, with a lot of solved examples (complex ones) step by step. The readings should also explain very weel what I'm doing and why I'm doing each step, and in the end explain the exercise as a whole.

The practice quizzes should bring very real life examples (as thouse of VBS tests) and they have to match de guide text.

The videos should be made only from the most comum doubts and mistakes in the practice quizzes.

While this was a good basic math, probability, and statistics refresher with good background material and reference documentation, it only scratches the surface of data science. I did like the problem solving style and the set theory this course encouraged, I did not find it sufficient to call a "data science" class. I understand this is may be a course prerequisite for other course, but alone I don't think it should refer to "data science".

The first two weeks were well paced, in week 3 I think too much is covered too quickly and in week 4 there is a further acceleration. That said, the course was good in highlighting the areas that I feel I need to work on and motivated me to take University of Zurich's intro to probability which filled the gap for the content from week 4 here. I think this might be a good refresher course for someone whose knowledge is not too stale.

I would give it a 3.5. Good for introducing you to the concepts you might need, but very bad at explaining them. It is understandable since it is a short course. Just bear that in mind when you enroll, if you want to explore a concept in depth you will need to look elsewhere. My main concern lies in the fact that the test were slightly harder than the topics covered on the videos, but still in the realm of manageable.

good subject matter choice; however, quality varied between the two professors. weeks 1-3 provided good clear lectures and enough practice questions; but week 4 had several confusing points in the lecture, then not enough practice. I really had to supplement my learning with outside videos and problems for week 4. but i passed the final test first time. thanks for narrowing down the maths needed for data science.

The final week, covering Probability, was pretty mediocre. A very strong weeks 1 and 2 start with a pretty steep decline towards the end. I picked up this course as a demonstration of core data science math skills. I already knew most of the concepts so I didn't have much difficulty, however, if you're looking to pick this course up purely to acquire these new skills, I'd suggest looking elsewhere.

Lessons 1-3 are ok. Everything is explained well and you can make the tests easily. 4 is very difficult and despite many trials, I was not able to make it. And because of chapter 4 I suggest you rather take another course.

There is also a technical problem, because the formulas are displayed in java script, so it is not easy to understand how the formula looks like, if you do not know the script :(

The first 3 weeks were great. The last week on Statistics and Probability was not in depth enough. Theorems were presented often without showing how to apply them. When examples were given, the teacher would skip over steps in solving them, and I was left wondering how he got from Point A to Point B. I've ordered a statistics workbook in order to better understand those concepts.

The lectures are very short and simple. Sometimes the explanations are not explained thoroughly. Students without background on the subject will find it difficult to apply the concepts in actual problems like in the quizzes. I hope you can improve your content, discussions, and quizzes so students without background in advance math can enjoy your course. Thank you!

The course was useful and well designed. Trainees can achieve a noticeable background of data science and gain a good vision about what data science is. However, It would make the course more comprehensive if the trainers provide some real life example questions especially when talking about the mathematical rules and formulas during the course.

Helpful overview and review if it’s been a while since you taken stats and probability. But really needs more practice problems with explanations to practice through the workflow on the last two weeks. The formulas and calculations get pretty intense. They have printable handouts that go with all videos that were very helpful.