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### 예술 & 인문학

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!...

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)

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.

필터링 기준:

교육 기관: Michał F

•Aug 30, 2017

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

교육 기관: benjamin.dubreu

•Sep 23, 2017

If you are familiar with the concepts in this course, it will be fine. If, however, you happen to discover them for the first time here, the instructors go so quickly in their explanations that you'll end up with a high level of frustration.

When it comes to statistics, fewer concepts introduced per video, and more examples of each concepts would have been a better approach for real beginners.

Finally, don't believe you've acquired the "math skills" necessary for data science just by following this course. In this, the title can be seriously misleading.

교육 기관: Bola T

•Jun 02, 2017

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

교육 기관: G T

•Mar 01, 2017

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

교육 기관: Mei Y

•Aug 27, 2017

Broad coverage of topics in a compact course. Useful for those looking for a refresher course. Could be improved by explaining where in data science the chosen topics would be relevant to provide context.

교육 기관: Danilo C

•Jan 17, 2018

First 2 weeks of the course is amazing, very good didactics. The second teacher does not use very good examples, and the thing starts to fill like old math classes, but overall is good. I will need to redo the last 2 weeks because i fill that I will not remember most of it so easy as the first 2 weeks.

교육 기관: Margaret S

•Jul 25, 2017

The class is good. However, the second half of the class zips through concepts that need a lot more explanation than is provided. Moreover this class would benefit from an optional tutorial on how to input factorials into a calculator as the answers on the exam go to the 8th decimal place.

교육 기관: Saurabh K

•May 27, 2018

Good for high level understanding of few of the concepts. But last week 4 tutorials are covered at very high level , it was quite difficult to understand probability topic without referring to other online tutorials. I wish more examples could be given in the tutorials to strengthen understanding.

교육 기관: Kyle A

•Apr 28, 2018

Good for beginners.

교육 기관: Lucas L S

•Jan 31, 2018

The course should be a guide text with very detail readings, with a lot of solved examples (complex ones) step by step. The readings should also explain very weel what I'm doing and why I'm doing each step, and in the end explain the exercise as a whole.

The practice quizzes should bring very real life examples (as thouse of VBS tests) and they have to match de guide text.

The videos should be made only from the most comum doubts and mistakes in the practice quizzes.

교육 기관: Neha B

•Feb 03, 2018

the course was really good. I just hope that we can get more practice questions in between the lectures so that we can understand the concept more precisely and deeply.

교육 기관: christopher w

•Feb 25, 2018

The first two weeks were well paced, in week 3 I think too much is covered too quickly and in week 4 there is a further acceleration. That said, the course was good in highlighting the areas that I feel I need to work on and motivated me to take University of Zurich's intro to probability which filled the gap for the content from week 4 here. I think this might be a good refresher course for someone whose knowledge is not too stale.

교육 기관: Jeff B

•Jun 22, 2019

Felt like the first 3 weeks were pretty good but the probability section needs a lot more detailed explanations and examples to make the information clear. For those that are already OK with this subject, it's probably fine but for those that haven't had much background in probability, this part was lacking.

교육 기관: Susmito R

•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.

교육 기관: Ashraf S

•Jan 17, 2019

This course dos not contain enough examples which needed to train and practice ,PDF is not clear enough and does not contain any problems to practice.

Thanks

교육 기관: Vaibhav J

•Feb 10, 2019

Found the title of the course mis-leading! School level Math skills are taught. Found the title to be similar to "click-baits"

교육 기관: Md. Z M

•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.

교육 기관: Saurabh S

•Jul 11, 2017

Week 1 and week 2 are good. rest of the weeks are very fast and not clear.

교육 기관: Egor M

•Jul 27, 2017

This course is very short. I've completed it in about 4 hours. Nothing was told about linear algebra, statistics, optimization. It is not enough even to learn Data Science.

교육 기관: A M A

•Dec 24, 2017

Probability part is good others are elementary math

교육 기관: Deleted A

•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.

교육 기관: Peter G

•Mar 04, 2018

I enjoyed the first 2 weeks. Weeks 3 and 4 were harder to follow. Too few examples, particularly in week 4.

교육 기관: Jonathan H

•Feb 08, 2017

Very basic course... probably won't teach you a lot of new things

교육 기관: Derek S

•Mar 30, 2018

last week was very hard

교육 기관: Numsap S

•Mar 21, 2017

Too basic. Should give an example on how these math skills are used in data science.