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

4.5
2,340 個評分
516 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.

476 - Data Science Math Skills 的 500 個評論（共 519 個）

Jan 20, 2019

Overall it's a good one. In Math part I liked it a lot but in Stat I think Prof should explain a bit more in depth and the content is not good enough.

Feb 07, 2019

The material covered was very useful for a beginner/intermediate course, however, the style of the presenters was not always very clear.

Dec 13, 2017

it's the foundation for data science, but these contents are too simple. I think it's not enough for a good data analyst.

May 29, 2017

a good selection of topics, but way too formula based rather than understanding based, especially in the second half.

Mar 30, 2020

Some of the quiz questions have mathematical errors (e.g. inside of a log cannot be negative) or are quite unclear.

Sep 26, 2019

The last module could have been done better. More examples to be included for explaining probability problems.

Aug 30, 2017

Basics knowledge, i liked first part about functions, but second was not quite good for me.

Feb 10, 2017

The Probability section could use more practical examples, I found it difficult to follow.

May 07, 2018

Last quiz is very hard and course does not provide the knowlege needed to resolve it.

Mar 01, 2017

The material is very useful, however, the second teacher is not the best...

Jan 26, 2018

It is more of an "appetizer" than a whole self-contained "meal".

May 30, 2017

The contents were ok, but the videos were a bit boring

Feb 24, 2018

Lost if it is a basic or a intermediate level course.

Dec 28, 2017

The materials could be more advanced for data science

Jun 02, 2017

last week is not good at all i didn't get it all

Sep 13, 2018

Probability concepts could be more descriptive.

Mar 31, 2020

I think some basic statistics should be added

Nov 29, 2019

the lectures of last week r very bad

Aug 28, 2017

too superficial to be usefull

Jan 11, 2019

1st 2 weeks were very basic.

Oct 19, 2018

It is too low level

Apr 28, 2018

Good for beginners.

Feb 23, 2018

Good!!

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.

Aug 20, 2017

The first two weeks are good. The material is explained in a fairly intuitive way. One can easily understand the theory. It is also explained why and how a presented concept is related to data science.

The last two weeks however are to shallow and abstract in the explanations. I had to check external websites to fully understand the material. The lectures also didn't prepare me good enough for the tests. Sometimes I felt lost and the video companions also didn't really help. This wasn't the case in the first two weeks. At the end I was able to complete all tests with 100% but only because I taught the material myself with the help of external websites.