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

4.5
9,297 個評分
2,111 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

VS
2020年9月22日

This course syllabus is great. It starts wonderfully. Week 1 to 4 is taught by Paul Bendich, and Daniel Egger the instruction is awesome. Effective way to refresh and add the Data Science math skills!

VC
2020年5月16日

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)

## 76 - Data Science Math Skills 的 100 個評論（共 2,090 個）

2020年4月17日

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.

2020年5月15日

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!

2020年7月11日

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.

2020年7月3日

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.

2020年6月11日

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.

2021年5月26日

I truly enjoyed the course! It is a good refresher and the materials are very straightforward as they cover the maths needed to begin our journey into the basics of machine learning. Videos are short, which I really appreciate! Instructors' handwritings were easy to read an the quizzes were also enjoyable (I'd personally rate the difficulty level of the quizzes around beginner to intermediate, so they are definitely doable).

2020年7月26日

Excellent course for beginners. It starts from the basics and goes up to the intermediate level. Excellent short and very well explained videos and exceptionally good practice and graded questions. These questions help students to think deep into the matter and provide the necessary stimuli of in-depth learning. Great course. I am much obliged to Coursera, Duke University and the instructors for giving such an opportunity.

2020年4月26日

From 3 courses I've taken so far, this one was the best, because it covers a lot from basics to complex math. By the end of the course it does try to cover very complicated topics, which if you don't have training in, you will feel the need to supplement from another resources, even though the reading section of this course helps a lot. Lectures on Khan academy were also very helpful in remembering lost concepts.

2020年12月4日

100 OUT OF 100 BECAUSE VIDEOS ARE AVAILABLE WITH GOOD QUALITIES + CONTENT AND EXAMPLES + RESOURCES MATERIAL i.e. THE PDFS ARE AVAILABLE WITH THIS COURSE MATERIALS FOR WHICH NO USE OF HANDWRITTEN NOTES IS REQUIRED .

THANKS A LOT MY ALL DEAR RESPECTED SIR + SPECIAL THANKS TO ALL FACULTY MEMBERS OF DUKE UNIVERSITY FOR THIS MATERIAL PROVIDING TO US

2020年4月19日

The course was easy and comprehensible as long as you have done basic maths at some point in your life. For those who don't I would suggest to go and take a calculus and statistics course and revisit. Otherwise, you would have to do some research by your own, in order to be able to follow. Keep in mind that if you do not see the exponents etc, change browser. Chrome seems to work better than my Firefox.

2020年9月5日

I did learn this course due to I found out a mention about it in an article on the Web. I had 3 higher eds with math, and I needed to get it again because I started to learn Data Science in Health Care Administration. Thanks to the lecturer, thanks to all who made this course availible online.I would like to continue with you! Highly recommend this course for those who need to study Data Science.

2020年9月17日

Great course to strengthen the basics before jumping into applicable approach on data science. The hardest part on this course is the week 4, the one with probability and bayes theorem, and it is advised to get supplementary information on bayes theorem and probability to avoid confusion. All in all, it is highly recommended to anyone starting to learn for solid understanding on data.

2020年12月30日

Overall this course I believe is deliver skill effectively. As I have forgot what is learned in high school due to lack of use in my life after come out from school, the Algebra session is very interesting and easy to learn for me Come to Probability session which is a totally new interesting field to me, I wish I have a better memory because it is not easy to learn in a short time.

2020年4月10日

I am fairly new to the field of Data Science and Machine Learning, and I felt like i had to strengthen my math skills, hence why I enrolled in the class. The professor did a great job explaining everything in detail, and brushing up on simple math terms. I feel more confident now to move forward into data science that I have a basic knowledge and understanding of the math concepts.

2020年9月3日

A fantastic primer on the basics of math related to practically every quantitative field. I hadn't touched probability since high school but now i feel that i am prepared to tackle intermediate probability problems. That being said, prepare to breeze through most of this course and then suddenly find yourself looking up advice on math stack exchange.

I love Bayesian statistics.

2020年12月3日

The course will introduce you to the basics of Mathematics needed in Data Science. If you have a STEM Background then the course would be easy for you. I personally find the quiz to be really good which will make you apply the knowledge you learned. Also, the course material is helpful and useful for future reference. Thanks to the Professors of the course and Duke University.

2020年4月26日

First of all I would like to thanks Coursera for providing the different types of courses by the world best instructors from the top universities. From this course, I get to know more deeply knowledge about data science maths skills .By, using those knowledge I can apply those in real life problem related to this.

Thank you very much Coursera for providing this type of platform

2020年4月8日

I totally liked this course for clear explanations and plenty of practical exercises. Some of them were not easy for me, but thanks to comments after mistakes I could finally find the right solutions. Just in the last week in the final quiz, there were no explanations, but maybe it was a problem on the site side. This course made me think a lot, and I enjoyed it genuinely.

2020年6月29日

I thoroughly enjoyed my course as both professors made the entire process of learning an excellent starting point for beginners as well as a wonderful refresher for those returning to the subject once again. I strongly recommend doing this course in order to better understand the fundamental concepts that are underlying the domain of mathematics in Data Science.

2020年6月10日

This is a good course for anyone who wants to brush their math skills. The explanation in the videos are clear and the video companions/pdf files are very helpful. I personally read the pdf files first and then watch the videos and proceed to do the quizzes. If there should be any improvement, I'd like to see more practice questions, especially after each video.

2020年6月8日

The explanation of concepts was amazing. But I feel more examples should have been illustrated, since the quizzes were really hard in the last week. Overall, a great Mathematics and Statistics refresher course. This short course will help you figure out where you stand and how much more work needs to be done with respect to your Data Science Math skills.

2020年8月2日

This course really helped me in refreshing my knowledge, especially at the theories of probability. First, second, and third module was okay, but in the last module (module 4), you need to study more comprehensively as there were too many trap answers. This course is a good choice for everyone who wants to begin their specialization in data science.

2021年1月24日

The corse is really good. If you had mathematics some time ago and wish to get started again, this course is for you.

The last two modules are much better than the first two ones, but I guess it's still a work in progress. Feedback and answers make a huge difference. I learned quite a lot reviewing my own mistakes with the help of the answers.

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2020年7月30日

Nice introduction with Probability and other mathematics. Good examples. For some, it might be too basic. I have not done mathematics of 3 years this course has helped me to remember different common rules and their application in data science. It has jerked my memory down. Thought, the probability module can be improved with better examples.

2017年8月27日

Succinct explanation of the basics. Take more time at the Bayes theorem. It is worth it. Work out all the problems and keep reading the PDF notes accompanied with the videos. All in all, a great experience for those who have missed some basic math in earlier education. I am onward to my next course in machine learning and data science. Cheers