# 學生對 杜克大学 提供的 Data Science Math Skills 的評價和反饋

4.5
2,205 個評分
491 條評論

## 課程概述

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material. Topics include: ~Set theory, including Venn diagrams ~Properties of the real number line ~Interval notation and algebra with inequalities ~Uses for summation and Sigma notation ~Math on the Cartesian (x,y) plane, slope and distance formulas ~Graphing and describing functions and their inverses on the x-y plane, ~The concept of instantaneous rate of change and tangent lines to a curve ~Exponents, logarithms, and the natural log function. ~Probability theory, including Bayes’ theorem. While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." Good luck and we hope you enjoy the course!...

## 熱門審閱

##### AS

Jan 12, 2019

Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)

##### PS

Jul 23, 2017

This is neat little course to revise math fundamentals. I generally find learning probability a little tricky. This course helped me a lot in better understanding Bayes Theorem. Thank you professors.

## 276 - Data Science Math Skills 的 300 個評論（共 482 個）

Nov 12, 2017

good

Oct 30, 2017

Nice

Mar 04, 2018

t

Apr 06, 2017

-

Oct 11, 2017

As it is now, the course is a much better resource for reviewing the material (which was fine for me as it was what I was trying to do) than for learning it first time. It would be much better if it had more of the same, which is why I am giving it 4 stars instead of 5. In my opinion, it is too brief; I hope to see a part 2 expanding on the material provided here. Many of the topics mentioned, and they really were mentioned more than really taught, should have been talked about in more detail. I've completed the whole course in about 4-6 hours over 2.5 days. It is a good attempt, but it is hardly a sufficient preparation for the field of Data Science; students looking to take the course should be aware of this.

TLDR: A nice and brief overview of many important concepts (sadly, missing linear algebra) which lay the mathematical foundation for getting into Data Science. Needs to be expanded upon.

Jan 15, 2018

This course was very challenging for me (I'm a musician). I wanted to review the concepts presented in this course to get back on track with my math skills. It was fun, but required me so much time to understand what is what and how to apply it to problem solving. Take this course if you are into Data Science or if you are a programmer who wants to plot data for any given purposes. If you are a musician, well... It will refresh your memory and maybe it will also have an impact on your music : p

Aug 03, 2019

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.

Mar 28, 2018

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.

Nov 11, 2019

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.

Mar 30, 2017

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.

Sep 18, 2019

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.

May 03, 2019

Good Refresher course. The material is on the easy side so you can finish the class in 1-2 hours. The last part of the class about probability was very good.

If you don't know anything before hand, this would be a good introduction to math topic that you would need to know, but not enough to stand on its own.

Jan 07, 2018

This is a good review of basic mathematical principles. There were some examples of how the concepts apply to data analysis, but there could have been even more. The explanations were clear and concise. There is not a lot of reinforcement of the material, so I ended up doing some additional study/review.

May 29, 2019

Great crash course. The latter units really ramp up in difficulty and the quiz/tests really made sure I was paying attention. There were a number of inconsistencies early on in the course. Although there were notices posted about them, it was still jarring to see/hear an example that was clearly wrong.

Jul 11, 2017

Enjoyed the first 3 weeks quite a bit. The probability lectures were not as strong as lectures in Weeks 1 through 3, however. I took the Intuitive Probability course offered by Zurich University to really learn probability well and only thenI was able to pass exams in week 4 of this course.

Sep 17, 2017

The Math instructor was great! I loved all his lessons. The engineering instructor teaches this final few weeks. I struggled with his teaching style and his penmanship. But, the topics covered throughout the course are great! The course notes given I also found useful I will hold on to!

Sep 08, 2019

The weakest coverage was definitely in the 4th week during the coverage of probability. One would be better off using youtube videos or another course as this overview was rushed and felt incomplete. The explanations and examples were just not up the standard set by previous weeks 1-3.

May 27, 2018

The videos and class materials are great for introducing students to all of these concepts. However, there should be more ways for students to practice things that they have learned in this class. Some of the modules were especially difficult because of the lack of practice problems.

Jan 19, 2018

Great fun brushing up all those basic skills! The quizzes were challenging. Additional reading resources might be helpful. Some later videos need a bit more explaining I guess. It might also be helpful to speed up the videos while the instructors are writing things down.

Feb 05, 2018

Is a great course for the most part. However, as it gets toward the more complicated concepts there are expanding holes in the explanations and the homework. Students enrolling in this course need to be ready to teach themselves more as the material progresses.

May 21, 2017

Although I previously studied these things I have long forgotten them or they WAY I was taught them previously was incompatible with Data Science in general. Do this course first if you want to start data science and your maths needs some work.

Oct 16, 2017

Course is simple yet difficult. It explains most of the concepts in simple way but the assignments are pretty hard to solve :) overall makes perfect foundation and provide necessary skills for data Science. More focus on derivatives will help.

Nov 10, 2018

I leaned a lot especially in probability. But I had to search around various other resources before I got the hang of Bayes theorem. Also a tree diagram approach to both conditional and Bayes theorem will help get to the understanding faster.

Oct 10, 2017

Great introduction to mathematical analysis and probability. I took it to refresh the concepts I had learned some years ago and it met my expectations. The quizzes, particularly the ones in weeks 3 and 4, are quite challenging.

Feb 27, 2018

The content of the course as a whole is interesting as a good synthesis of basic skills, even though the content of the weeks 3 and 4 lacks of clarity compared to the content of the weeks 1 and 2.