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

4.5
4,907 個評分
1,095 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

##### VC

May 17, 2020

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)

##### RS

May 06, 2020

This was mostly review for me though probability especially Beyes Theorem derivation was new. The instructors provided clear often refreshing ways to look at material.\n\nThank you for a great class!!

## 26 - Data Science Math Skills 的 50 個評論（共 1,099 個）

Apr 26, 2017

A tremendously useful primer on the fundamentals of data science math. This course is a particularly good option for individuals who have seen some amount of calculus and algebra but haven't used those methods in a long while and need to review. Thorough, easy-to-understand material.

I would suggest to the course facilitators that they develop the provided lecture notes -- already a useful tool -- into a full-fledged text. I'm not suggesting something much longer than what they already have, but simply taking that document and adding a bit more rich content. While the notes are useful for more carefully studying the math being done in the lectures, even a bit of effort putting some pedagogy into the notes and combining them into a single document (which I did for the sake of printing) would create a hugely valuable resource.

Mar 09, 2018

This course is designed for those either without a college level math background (calculus, probability, etc) and thus need an introduction to fundamental math skills or for those who need a refresher. This is not a course that teaches data science, nor the math of data science (linear algebra, random processes, algorithms, etc). But rather it teaches the math behind the math of data science. It reviews the basics of sets, plotting, sigma notation, derivatives, logarithms, mean and variance, Bayes theorem, etc. It is a gentle introduction to basic math skills that everyone should have. This is a course to definitely take as a refresher or before venturing into more higher topics such as collegiate math, data analysis, machine learning, computer science, engineering, etc.

Jan 31, 2019

I learned many new things, ideas, knowledge,and skills from this course.I am very much thankful to both professors for teaching about all of those interesting lessons,providing many more things. now, I am able to give all of the answers frequently which I learned from this beneficial course.

Apr 23, 2020

The course has limited resource to understand. This course content is not sufficient to understand the topics. But that is fine as we come to know what we need to learn .Then , We have to put additional effort to understand the topics in external sources like textbooks, Internet, youtube.

Jul 24, 2017

cannot believe I took a programming course without doing this - the math was taking me so long and it was because I hadn't finished high school math a decade ago (our school didn't require it) - really thankful to have found this course!

Nov 07, 2019

Every part covered gives a good introduction to the world of data science as intended. However in my personal opinion the part on probability was covered a bit hastily, though the quizzes will force you get some in-depth understanding

Sep 11, 2017

This is a very interesting course for those who have not used math for many years and now want to pursue the field of data science. The basic concepts are presented coherently and understandably attracted me throughout the course.

Apr 12, 2020

It is really good data science math course, all described topics are highly important to know for everyone who need to know about data science. if anyone want to know about Data Science I will recommend to join this course.

Mar 07, 2019

As a non-native speaker, the first three parts are helpful in getting into math terminologies and reviewing basic math knowledges. The essence is all about the last part, which might be a little tough for new learners I guess.

Dec 16, 2017

A great refresher course and a range of interesting and foundational concepts. Would recommend to anyone who has prior experience with calculus and probability theory and is just looking to remind themselves of key concepts.

May 02, 2020

Great option to get back to the Math worked, reviewing the basics of what needs to be known when working on data science and see where you need to put more effort. Hoping this helps while I continue taking other DS courses.

Feb 13, 2020

It helped me reviewing and learning interesting mathematical points that will help me understand more about my Machine Learning course.

I believe the last week, about probability. could be more extensive and made more clear.

Feb 17, 2020

This was a great beginner course on some of the math you might see in Data Science. I'd recommend this course to anyone that might not be confident in math who want to start a career in this field. A great refresher!

Mar 04, 2018

Fantastic course, especially when paired with or done before Andrew Ng's Machine Learning course as it matches up quite well! Thank you for the detailed guidance in the practice quizzes on incorrect answers as well!

Dec 17, 2017

This course gives me the basic conceptions about the mathematics, especially parts about calculus and possibilities, however, if would be great if there are samples or basic practices related with the data science.

Aug 20, 2017

This was an excellent review of the basic mathematical concepts useful in data science and machine learning. Thank you very much for the very concise and clear explanations of the various topics! Much appreciated!

May 29, 2017

very nice course, and a good starting point to catch up data science and computer science math-skills. Helps to bring some of those rusty concepts back into memory, and from there you can expand further ...

Apr 17, 2020

Hi it is very helpful to me. Concept is properly explained. I enjoyed learning process. Expect some more courses on data science as well as on python which involves real time application.

Thanks a lot.

Dec 11, 2019

First 3 weeks were easy going and the last week was a bit more challenging. I think more examples could be included in the lectures to understand Bayes' Theorem at the most fundamental level.

Apr 28, 2020

It was a very good opportunity to go through the course, and the content was good. I can say I definitely learnt a lot in this course. Thanks team and kudos to great work you guys are doing.

Mar 07, 2018

Looking forward to advanced courses on Linear algebra, eculidean geometry that would make the concepts of vectors, matrices, plane and any application of those in the data science problems.

May 04, 2020

It covers all basics of mathematics and of-course intermediate concepts from Mathematics which are essential for data science in general, and very useful for data mining, data storage etc.

Jul 13, 2019

The first two weeks of the course were great! The instructor was very clear in his explanations and made the material very intuitive. The video companion pdf's were also very well written. But from the third week onward, when the other instructor took over, not only did the explanations suffer significantly, the video companion material also ceased to be of much help. He did not explain any of the intuition behind any of the formulas and he didn't even try to explain the intuition behind when and where the formulas would apply. I didn't take this course just to be given a bunch of formulas. I really wanted to understand the material because I knew these are foundational concepts that needed to be mastered. Khan Academy explains a lot of the material of weeks 3 and 4 much better. I really wish someone had explained how the version of the binomial theorem that was presented in this course is related to the traditional version that we learned in school while doing binomial expansions in algebra.

Oct 05, 2019

The first part of this course was great. It was the right level of material, taught simply and effectively with quizzes and exams that were on par with the taught material. The second half was not so great. The teaching style of the second teacher did not convey the material as effectively as the first teacher. Also, I felt that the week 4 probability quiz and final exam had material way beyond what was taught during the lesson. There should have been some exercises to warm us up and get us to the difficulty level of the final. It felt like going from 0-100 mph. Overall because of the stark difference in teaching and difficulty of the final exam of part 4, I can only give this course three stars for the great start.

Mar 08, 2019

For someone with a Computer Science background at the undergraduate level, I find the contents basic. However, the intention of the course was to give a refresher for data science professionals who find the mathematical jargon frequently used in practice hard to comprehend. In this sense, the first half of the course taught by Prof. Paul Bendich were good. The second part of the course taught by Prof. Daniel Egger needs a lot of improvement in content delivery and better explanation. The quizzes on probability are challenging and enjoyable. Also, when I took the course as on March 2019, there wasn't any activity on the discussion forum. It seems there are not many students taking the course with me, and it also wasn't monitored by the course staff.