Retour à Data Science Math Skills

4.5

1,787 notes

•

411 avis

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.

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par Robyn J

•Feb 08, 2017

This course is very strong with respect to presenting the concepts you need to know for data science. It is extremely WEAK in terms explaining those concepts. If you are like me and did this kind of math back in the 70's and 80's but have not used it since, be prepared to seek sources outside Coursera in order to understand the material and pass the quizzes. The instructors leave out explanations and skip important points leaving you confused about the concept.

Example: In the Permutations and Combinations sections, "results" of calculations are thrown at you with no explanation of how the instructor got the answer. 10 minutes later, totally as an aside, you get the explanation. The course is not taught in such a way that A leads to B, B leads to C, and C leads.....; instead the instructor will tell you about C, might explain A, and forget about mentioning B until the graded quiz. That is why you will need to fill in the gaps using websites like betterexplained.com or kahnacademy.com.

The student is better served by looking at the syllabus and then going to either of those sites - where the explanations are worth your time.

In addition to failing to present steps in a logical order, the course often teaches at an extremely basic level but tests at a much, much higher level. Again, to get to the higher level of understanding needed to pass ANY of the required, graded quizzes, the student will need to heavily utilize outside sources. The explanations on the practice quizzes also fail in many cases to thoroughly explain why an answer is correct.

Then there are the issues with Coursera itself, the course navigation using Chrome is quite bad. If I did not constantly monitor what part of a course I should be in versus what part of the course automatically loaded next, I often found myself taking a quiz for which no lectures had been presented. The TA's response to my complaint was flippant and WRONG. She then closed my question and I could not respond or ask for more details.

If I had it to do over again I would invest my time and money somewhere else. In my opinion, Coursera should rescind the instructors' rights to charge for this course until the instructors improve and meet higher teaching standards.

par Roberto S

•Jul 24, 2017

For newbies, the set theory, real numbers, basic statistics and so on are quite well explained. The intro to probability, however, is shallow and quite confusing. It lacks some real-life examples to offer a better grasp of the theory. Coins and dices examples are a good start, but made up examples without a real base are not clarifying at all.

par Marcel S

•Apr 30, 2017

Week one starts with interesting material that relates probability to data science. Unfortunately as the course progress the course material and videos become less and less helpful. Ultimately the student has to visit other web sites and youtube to actual learn the expected material. The course notes are next to useless and the video are equally unhelpful. I am sure the teachers know their stuff but they have no idea on teaching it clearly based on the material presented in this course. Avoid this course, and head over to KhanAcedemy and complete their probability and statistics program and you will actually learn all the material in this course with a ton of examples and top class videos.

par Danuel R

•Apr 01, 2017

Difficult content not explained well by the presenters.

par Abhay G

•Jun 17, 2019

This course is very useful specially for me that clear all fundamental very sharp.

par Archana T R

•Jun 10, 2019

Pretty good revision of basic maths concepts.

par Shabab K

•Jun 01, 2019

Good course. Last quiz was extremely hard though!

par Deep R S

•May 29, 2019

Course contained simple maths, algebra, summation, mean and variance

par Edward I

•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.

par Priti B

•May 28, 2019

I came for this course after working on data science for sometime. While initial 2 weeks were easy and known, last 2 weeks were really helpful. My probability concepts become much clearer after going through the lecture and tests. Very precise and clear course. Thanks a lot!

par Akhil K

•May 27, 2019

Good

par jawad s

•May 26, 2019

This course help me in an understanding of coordinate as well as statistic.

par vani s

•May 25, 2019

Really Really very interesting from the beginning till the end. Instructor videos are excellent. Thank you so much and waiting for these kind of courses in future.

par Phúc P

•May 19, 2019

A very helpful course for starting data science.

par Syed A I

•May 16, 2019

Excellent courser

par Laxman L

•May 14, 2019

well explained

par Akhil E

•May 14, 2019

Excellent course to refresh some basic math concepts

par Francisco A

•May 10, 2019

Great introduction to the required math skills necessary to apply data science. Very useful

par Mohd F E B A

•May 09, 2019

Though that this course was too simple but actually it is quite an eye opening and refreshing for the last two topics. Well done!

par Nagaraj A M

•May 09, 2019

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par Swaviman K

•May 08, 2019

Very well explained concepts. The probability portion was the best. Baye's theorem & Binomial theorem were very interesting. I had a very nice learning experience.

par Trong T L

•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.

par Abdulrazak I

•May 01, 2019

It was a nice course and well documented

par Rodolfo S

•Apr 23, 2019

Great course! Great material! It has been fun to learn and beginning a data science path with this outstanding introduction.

par Mike

•Apr 08, 2019

Great!

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