good

Actually the lessons from first three weeks are really basic (junior to senior high level), and sometimes I can't find any strong relationship with data science. And the fourth week is about probability theorem including the marginal/joint probability and bayesian theory without introducing other fundamental concepts, which could make the student quite confused sometimes.

There are several typos by the first teacher, which most are all corrected but quite disturbing. And the handwriting of the second professor is sometimes sloppy. I'd rather check the "video companion" before taking the class. BTW, they are really good and concise to summarize the concept and understand what the professors are talking about.

About the quiz/exam, most are good with explanations. But a lot of question require electronic calculator. Some question do not provide basic value of number like log(2) or which is quite annoying.

It's not good as imagine, but it does not take much time to finish.

Weeks 1 - 3 can be understood with relative ease depending on your math skills. Week 4, however, is quite tough because both the instructional videos and the notes are difficult, if not impossible, to understand. I had to resort to resources both within and outside of coursera to understand Week 4, specifically YouTube, Khan Academy, free math tutorial videos from my public library, and a separate course on Coursera. I spoke to customer service, but they were unable to give me some sort of credit, or free month, or anything.

Coursera, if you're listening, please do a better job at quality control. Just because a professor is from a top university does not mean he can teach well.

This class fails to give a single explanation as to how the math skills will apply to data science. The first three weeks are a nice basic explanation of some of the math that will be needed. If you haven't done coding before or have some background in coding, you will have no idea where this class is going to be applied. The fourth week is the worst explanation of probability you can imagine -- opaque derivations and almost no explanations. I do not recommend this class as it fails to address the "why" of the title -- how does math apply to data science.

i passed all quizzes and exams at 100% most of them in one try.

presentations were a bit sloppy, and often i found i understood the concepts, but not how they were presented.

I did learn things from the course, but the experience could have been a lot better

especially week 4 was problematic, the bayesian probability and inverse probability was hard to understand from the videos or the notes alone, or in combination.

notes for one of the video had only notes for about the first half of the video, so no notes for the rest.

The content is OK; the execution isn't quite ready. Most is fairly basic, but is necessary and potentially a good review. But the course comes across like a first draft. Mistakes in videos are not re-recorded, but called out with a disclaimer. I believe there are two errors in answers to practices and quizzes, but it's possibly my own mistake on one. I noticed one instance where the correct answer is in a different font than incorrect answers. Overall, OK content but not very polished. It could use a second revision.

The first 3 weeks are quite good... but then it makes a gigantic leap on the 4th week. Please update the explanations on Bayes and the examples... they are not optimal. Judging from the comments I have seen, I am not the only one.

Thinking about it, I think maybe it would be worth to spend more time with probability and a bit less with the other stuff or even add another week... definitely probability in one week is a far shot... and it is key to understand data science correctly

A pretty good course even if week 3 and 4 are very difficult for beginners.

A few improvements are urgently needed:

-There are mistakes in the quizzes, which mistakes have been pointed out by generations of students for months/years in the forums, but have never been corrected. Such a disgrace and waste of student time!

-Also using Chrome makes you unable to read the formulas, which should be said in the course outset.

At week 4 the course was covered in a rush. This course could have been much better if the instructor could have taken the time out and walked the extra mile to simplify the concepts for a larger audience. I already had previous rigorous treatment of Probability theory hence didn't face many challenges. But I have empathy with students enrolling in this course who don't have prior probability background.

Course has misleading title. It has no strong connection to data science problems or examples from the field (except confussion matrix). First 3 weeks are simple math. Third one is very brief tour to probability with quite brief explanations which will not be enough for beginners to complete the assignment. There are also errors in the asssigments which I had reported.

I will not recommend it.

Instructors were knowledgeable, but I found the lectures to be a theoretical example, followed by a very simple real-life example. Then when you take the quiz, the questions are SIGNIFICANTLY more complicated than what I was ever taught in the lessons. Some worksheets of sample problems that escalate up to the difficulties seen in the quiz would have been very helpful.

The course content was very basic. Especially the first part of the course.

The later part(probability) of the course was very theoretical in nature. Typical problems in quizzes and examples as you would find in any mathematics text book. Being Data Science Maths skills course, I was expecting some real life example or even the mention of data science during the course.

T​he first part in the course in too basic, but atleast the level of task is equal to material.

T​he second part is too short for such a complicated topic. And lack of example doesn't help to solve the problems after each week. I had to check other sources for more clearer explanation.

O​veral the course doesn't cover the topic, it just has a "loud naming".

The course started of well paced but began to get complex and hard for me to pick up the logic. i clearly had a bad experience especially in probability part. could have used more understandable examples and explanations . although its said that this course is entirely for beginners, i feel its best suited for people who comes to refresh the topics .

After the second week, explanations become too abstract without a concrete explanation of how relates with the real world. Also, the examples are too short compare to the problems that are included in the quizzes. It will be way more interesting to learn the explanation of the quizzes than the abstract examples during the presentations.

Some useful concepts, but several of them, especially in the last week of the course, were very vague and did not give examples on how to use them to solve problems, which is the point of the course. If i wanted definitions and formulas I can just google them. The whole point of a video is to teach me how to apply it

The initial modules are insightful and helpful. But I had a lot of problems going through the material in week 4. The instructor struggles to make the content engaging and the videos often end up sounding very monotone. There's a big gap between the material discussed and the questions asked in practice.

The course is fairly easy and unchallenging. It's like an introduction in maths for high school students. I was expecting harder maths related to data science and/or machine learning, but this is just a review of high school maths. Not entirely a waste of time, but disappointing.

baye's theorem and the binomial addition to it should have been explained broadly, this is a multi country based program , people from different country access it. hence each and every formulae and colocations should be explained better and write-in a better way.

Very rushed presentation. Blows right through a lot of fundamental concepts without a deep enough explanation or enough practice material (especially in the last two weeks). I feel like completing this class will require supplementation with better instruction.

I was attracted by the syllabus (substance) but I found the presentation of the teachers quite disturbing (form); bad calligraphy, some mistakes, poor explanations. Anyway I completed the course and it will be useful as a general introduction to the topics.

As a stand-alone course, this is perhaps only for folks with above-average IQ. There was hardly any attempt to explain any of the concepts in a new/simple/intuitive manner. I wonder what the other students saw in this course resulting in the high rating.

The first three weeks had explanations that made sense (i.e. helped me learn the concepts). However, week 4 did not have enough material and it was really hard to work out what was going on, so I had to resort to Khan Academy and You Tube!

The probability section left many serious gaps in information compared to the test. I had to take the exam multiple times, and even after restarting half of the class twice. I'm not usually one to have to do this for a class.