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.

Keep in mind that this is meant to be an introduction to some of the math topics used in data science, it is not a comprehensive course. The course needs to include worksheets with practice problems for the students to practice. The instructors do not use enough real-world examples to demonstrate how the theory is applied.

je pense qu'il manque quelque définitions ,par exemple , pour dire que la probabilité d'un événement est égal à la somme de probabilités d'intersections de cet événement avec d'autres ,mais en fait on peut dire cela sauf si les autres événements forment un système complet d'événements. mais en général ça reste utile .

The course videos for the topics for Week 3 and 4 are not well explained. Even some of the questions in the quiz are not written in proper format. Please look into this and make changes to the course. Otherwise the syllabus of the course is well designed and the probability questions are of quite high standard!

Felt like the first 3 weeks were pretty good but the probability section needs a lot more detailed explanations and examples to make the information clear. For those that are already OK with this subject, it's probably fine but for those that haven't had much background in probability, this part was lacking.

The math went from extremely easy in weeks 1-3, to very challenging (with insufficient explanations) in week 4. I watched the videos from weeks 1-3 on 1.5x speed, but even going back to normal speed for week 4 was not enough. I had to find external resources to provide additional explanations for week 4.

The first half was planned and organized. The second half seemed haphazard. Examples were a little hard to follow. Quizzes were fine and seemed to test the material presented. I have only taken three other courses (4 total) and this one seemed a little rushed and the second half was created on a whim.

First 2 weeks of the course is amazing, very good didactics. The second teacher does not use very good examples, and the thing starts to fill like old math classes, but overall is good. I will need to redo the last 2 weeks because i fill that I will not remember most of it so easy as the first 2 weeks.

Good for high level understanding of few of the concepts. But last week 4 tutorials are covered at very high level , it was quite difficult to understand probability topic without referring to other online tutorials. I wish more examples could be given in the tutorials to strengthen understanding.

The class is good. However, the second half of the class zips through concepts that need a lot more explanation than is provided. Moreover this class would benefit from an optional tutorial on how to input factorials into a calculator as the answers on the exam go to the 8th decimal place.

The course was okay. Some fundamentals like logarithms was clear to me. However, they did not do a very good job in explaining the probability section like Bayes' conditional probability and binomial theorem in a clear and concise way like it was done with the other topics