Back to Data Science Math Skills

4.5

1,950 ratings

•

440 reviews

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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By 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.

By 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.

By 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.

By Danuel R

•Apr 01, 2017

Difficult content not explained well by the presenters.

By Mukund B G

•Dec 04, 2018

Very good informative, surely has helped me understand probability more intutively.

By Ramneek k

•Dec 23, 2018

Great Course, really refresh my math skills

By Sai K G

•Dec 24, 2018

Good

By Gustavo L R

•Jan 28, 2019

Good!

By Kasidis S

•Jan 04, 2019

Learned a lot from this course, thanks :)

By Yojana S

•Jan 31, 2019

I have got various knowledge from it. We have learn various lesson s of math. I am thankful for the professor who teaches us this things

By Gitashah

•Jan 31, 2019

First of all thanks to the data science math skill because i learned many new things,ideas,knowledge and skills from this course and more thankful to professors because of them i am able to give all the answers and it was too much interesting to do .

Thanks to all the teams of coursera as well as to the data science math skill......

By Merishka a

•Jan 31, 2019

I like this course. it is very intersting. Thanks for course.

By Ritima B

•Feb 01, 2019

Really a great place to get a free education. I already complete a course and am looking forward to complete my second course.

By srijanapuri

•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.

By Preeti A

•Jan 31, 2019

Learning this course I have gain many new and interesting skills. I am very much glad to get the knowledge from two professors and they gives me more knowledge on those interesting courses. I was able to do the answers of the given courses.And I THANKS them to give me such opportunity to do these courses.

By shruti b

•Feb 01, 2019

I have learn many things from this course such as algebra, equations,and other math problems. It has given me many information .

By Saida S A

•Feb 02, 2019

Great course

By Qicheng S

•Feb 03, 2019

Nice Course, Looking for specialization bundle on this one

By Mai V X

•Feb 06, 2019

It's very good to learn this course, so amazing.

By LI M

•Nov 09, 2018

good class

By Valerii M

•Nov 11, 2018

Great course!

By Joy G

•Nov 13, 2018

This course from course era has given me new opportunity to explore and has given me confidence in data science ,

By K H S B

•Jan 17, 2019

Excellent course. Very detailed explanation of concepts.

By Bijan K B

•Jan 17, 2019

Thanks for sharing the course details and subsequently facilitating the course.

By RAJESH K

•Jan 12, 2019

I love the way teacher, teach me.

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