First 2 weeks were really good, all well prepared structured simplified and explained in details. But last two weeks were really really bad. I had to spend 10 times more time in other sources like youtube etc. to understand what was happening there.

First it is very easy and the last week is difficult. There is no relationship between the material explained and what is evaluated. The course is subject to much improvement.

Audio is weak. Bendich is probably a good researcher, but not a good teacher. Doesn't make any effort to speak clearly, tone of voice is that the subject matter is beneath his genius, he's only "teaching" the course because Duke ordered him to teach it. Disappointed. I just copied down the curriculum then watched it on Khan. Sal Khan speaks clearly and covers the same boring 10 minute lecture in a lively half the time. Thanks anyway Coursera

Boring

I just finished the Data Science Math Skills on Coursera which is taught by Paul Bendich and Daniel Egger. Overall I learned a lot from this, but most of the stuff I learned already in Algebra class. For example, one thing that I already learned was the definition of infinite numbers on the number line.

One new thing I learned was about sets, which are a way to group numbers efficiently. It makes a big set of data easier to read and process. I also learned from this course is something called sigma notation, which is a way to solve a certain type of equation.

If this sounds really technical, don’t worry. Honestly, the course was less about doing math and more about learning how math is related to data science and some basic techniques and definitions.

Overall this course surprised me because I thought it was going to be a little boring, but it turned out alright. The only bad thing I would say about it is that Paul Bendich made a quite amount of errors in his lesson, causing Coursera to pause the video and edit it

If it is not for Dr.Paul Bendich, I would not have even continued with the course, let alone complete it. I wish I had such a teacher during my high school/college days. If I would have had one, my love for Mathematics would not have died. Dr.Paul Bendich is a God send. I thank God for making me attend this course. I am starting to love Mathematics again. I missed him during the last two weeks though. Dr.Egger was good. but for a student like me , Dr.Paul Bendich would have made a difference. different types of students need different types of teachers that suit them, right?

I am looking forward to more courses from Dr.Paul Bendich. Kudos to you Professor, I thank you for simplifying things, explaining things in such a way that even a lay man like me can understand and making me complete this course and rekindling my love towards Mathematics. I thank God for sending you.

So, I did well with Data Science Mathematical skills. First thing I did was the basic notions of theory, intersections, statistical quantities, Cartesian plane, measure distance and finding the equations of lines. So many vocabulary to go through, but a lot easier to understand. With any concepts, here is the real-world problem, turn to exponents, logarithms, rate of change for continuous growth, and much more. The final week is a lot difficult, but I finally did. I really did my best and focus what problems should come up. Probability and Bayes' Theorem. Those two are very important for me, but with certain questions and answer I know very well. This takes practice, but with enough effort that I made an improvement, I passed all grades. Though it's not always perfect, but I know what to do. I enjoyed this subject, pretty much I would say. Until next time.

I had my degree in Mathematics in 2009 from a university in Indonesia. Joining this course was a refresher for me. I know that some people don't like courses with hand writing but I LOVE IT! This really reminds me of my time in Uni and the best part is, both Paul and Daniel really helped me to understand the concept completely! When I was in Uni, I got good grade because I'm good with exams however I was just remembering formulas and I didn't really know how I can apply it in the real world. Now that I re-learn it, I just fell in love with Math all over again and I understand the concept much better. It's really good to know how to apply Math in the real world, which is for data science, data analysis and machine learning. Thanks a lot, Daniel & Paul! <3

Well this is my first course at Coursera and I really liked it... the way of explaining things and and the examples of using such basic mathematical concepts in real world gave me much better understanding of the topics that I already did in school... the level was moderate but then towards the last module this becomes actually fun and challenging for a high school student... I really appreciated the probability stuff.... and the level of graded assignments kept me liking mathematics even more... Data science is really nice way of explaining mathematical concepts that seems boring in a creative in a more logical manner... thanx Duke university for this course much appreciated. :)

The course overall was great. It was well taught-- very relevant and clear for the most part. I found the Probability lectures hard to follow. It seemed you need to know a lot of probability theory beforehand. Also the videos were too short in this sections and went very fast. The videos need to be longer, with 20-25 minutes and with more examples. The quizzes in this section were the hardest because not many examples were given in the lecture. Overall though I feel accomplished and feel I can tackle the math that comes my way when I pursue my data science degree. I will certainly recommend the course to my friends who wish to have better knowledge in mathematics for data science.

The course is a prerequisite for a Data Science course and its aim is to empowering your math skill :) With this purpouse, the course covers important mathematical topics; it can be used for advanced learners as a revision and a recap of fundamental subjects but someone may find it a little bit boring. I love maths so I really had enjoyed the course. For me, the last part (about probability, Bayes theorems, etc...) was the more challenging and interesting but I had also appreciated the first part with the funny explanations of prof. Bendich :) I think that the pdf companions are really useful to follow the lessons better.

The course has truly been helpful in showing me my level of understanding on the topics, as like all the other reviews it was a great refresher and more so it was truly helpful in helping me see areas i needed to improve on to become more advance in mathematics. i definitely recommend this course for those who want an understanding of the mathematics that is used in data science. this course by no means is an all you need math course to be successful with data science, but more of a stepping to stone or guide in my opinion in finding the right path to take to become far better in mathematics for this field.

Este curso lo recomiendo mucho a quienes estén interesados en refrescar sus conocimientos de matemáticas para pasar a cursos de estadística o data science. Es muy compacto por lo que los temas se tratan de manera concisa, pero realmente se avanza si se invierte el tiempo necesario. Yo estoy interesada en la estadística y mi campo es la lingüística, así que me tocó trabajar muchas horas haciendo cuentas en el papel y en la calculadora, buscando cómo hacer para sacar las distribuciones binomiales y las funciones básicas, pero me pareció al final que he dado grandes avances, me encantan las matemáticas.

The best course in my opinion. But I think it might not be suitable for everyone. For beginners and those who are not strong in mathematics in general, I think it will be difficult to master the course. But if you have good mathematical abilities and want to go beyond elementary mathematics, you will not find a better course. The best thing about it is that each topic is covered in real situations and tests really help to consolidate the knowledge gained. And for this I want to thank all the organizers and instructors of this course. Thank you!

While most of material is well known, it is presented in a great way, so it is a clean and smart refresher for Sets, basic Algebra and notations, Cartesian geometry and functions, and derivatives. I knew the material about logarithms, exponentials and probabilities, but I felt that I knew it better in the end of this courses. Material is great, and teachers are very clear. I wish they came with more material about calculus (matrices), vector spaces, Lagrangian, Hessian and so on, which are also really interesting in Data Sciences.

This course offers a great refresher of the FUNDAMENTALS of Linear Algebra , Calculus and Probability.

Do note the strong emphasis on fundamentals.

All lectures are well produced and the material put forward in an unambiguous and layman language.

The concepts presented are very easy to grasp , all thanks to the brilliant efforts of professor Bendich and professor Egger.

This course , along with another course on Calculus would serve as a great starting point for all data science enthusiasts and I strongly recommend it to everyone.

I found the first half of the course quite easy, as it was a refresher on the math that I managed to learn and retain as a high school student. However as I progressed through the course and found myself revisiting calculus and statistics concepts I found it challenging as I hadn't so much as touched a mathematics textbook since I graduated from university. That said I found this course excellent at understanding the mathematical principles on which data science foundations are built. It's definitely worth taking in my opinion.

This course was great! The first two weeks are relatively easy, but during weeks 3 & 4 you're going to have to watch some youtube videos on natural logs & probability. I recommend videos by StatQuest & the organic chemistry tutor.

I've found that this is true for any course that is modestly challenging, so it didn't really bother me much. I would have liked a few more videos of the teacher solving some example problems, but since there are thousands of examples of this on youtube, you shouldn't get stuck on any quizzes.

I learned a lot through this course. Set Theory,it's applications ,many formulas,functions,graphs ,probability and it's applications etc etc..I was able to study everything very well.Teachers taught well.it was a good course and also a good experience.I was able to know a lot of things. It was a kind of class where everything could be understood. The teachers explained everything very well.The examples given was more helpful.Through this course I was able to do each problem better.Thanks to the teachers who taught.

One of the best course, i have ever learnt. Even though i have been learning the Data Science for the last few years, i had no idea how the algorithms are working in technical. Which i was always skeptical. But honestly, now i am able to get things really faster than before. I am very happy, i have joined this course. Thank you so much for coursera to bring this course and importantly thank you so much for the professors to explain things in an easy for the people to understand. God bless you both and your family.

I thoroughly enjoyed taking this course because of the effective syllabus that reviews the math skills for Data Science. I liked having both Test and Graded Quiz to check the understandings of the subject.

Test Quiz gives good feedback on both correct and incorrect answer that helps to compare the problem-solving strategy and solution of the students with the correct solution.

Graded Quiz gradually becomes more challenging and the week 4 graded quiz is the most challenging quiz of all the graded quizzes.

I enjoyed the course content and lectures. The quizzes were a good test of understanding. I was wondering if there could have been a few more additional lectures and practice problems on probability. I request the team to check the answer to the 11th question on the last quiz of week 4.

Prof. Egger's lectures were very interesting and I only wish he had a larger writing board or apparatus. Thank you for getting me interested in a subject that is not my core area of work!

It was exactly what it said, math skills for the Data Science. Standard of problems kept increasing and became more and more challenging. I was able to finish the first 3 weeks in one day, because of my physics masters, I had previous Maths training, and that came handy. For the fourth week, the probability was extremely useful and challenging. I would recommend this to all future data scientist, especially if you are not coming from the Physical science background.

The learnings are very broad meaning, it is not only applicable in the field of data analytics but also in a the filed of mathematics, sciences, and statistics in my opinion. Thank you professor Daniel Egger and professor Paul Bendich for the amazing efforts, like for the amazing lectures and putting the step by step process of how to solve certain problems in your quizzes and also the of copies of the handouts which made my learning more conviniet.

I never thought I could do math, that I just didn't get it. In this course I was doing math stuff that I considered was way above me. While I still have some difficulties with the more advanced concepts such as logs and "where to begin" with probabilities, I still have a foundation in these that I actually understand. Knowing my inadequacies I can go on and study those, but thank you so much for making an easily understandable course.