Back to Data Science Math Skills

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9,655 ratings

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2,188 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!...

VC

May 16, 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 5, 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!!

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By Prerna S

•Jul 10, 2020

good

By Nagraj t

•Jul 6, 2020

good

By Nishant S

•Jul 4, 2020

nice

By Perumali S

•Jun 27, 2020

good

By LIJIN W

•Jun 16, 2020

Nice

By AVINASH K

•Jun 8, 2020

Nice

By Labib U

•Jun 7, 2020

good

By AVALA S

•Jun 2, 2020

Good

By Sunil R

•Jun 1, 2020

Gooo

By Mitesh M

•May 13, 2020

good

By TEJASWINI D

•May 7, 2020

GOOD

By Prateek G

•May 4, 2020

good

By SREERAM S

•Apr 10, 2020

good

By Fariha A S

•Sep 1, 2021

4

By Sakshi B

•Jul 21, 2021

i

By Jay Y

•May 7, 2020

.

By Amin A

•Sep 4, 2019

.

By Nagaraj A M

•May 9, 2019

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By nikhil k

•Feb 15, 2021

well the initial part of the course is very basic .. too basic.. the course doesn't scale up with the first 3 weeks. but the instructor is clear and makes concept easy to understand. but things change in the fourth week. the course shifts gears from very easy to intermediate. without much guidance.. or examples

math skills are to be practiced i hope the instructors level out the difficulty level in the course. An ideal math course should have many examples to practice with constant involvement of the instructors , support guys.

just 5 or 10 problems doesn't get you much and when asked to pass with 80% is tough.

. i left the course in week 4 and again completed after i understood week 4 content better.

this course doesn't have many many of the math skills required for data science.

ideally a math course should scale up from simple easy to intermediate to hard and later challenging questions and final assignment should have a combination of first 3 and passing of 70 to 75..

so the course requires

a. more examples for practice with solutions atleast 20 -25 both solved and unsolved

b. more math topics to make it more comprehensive for data science

c. more involvement overall

By Brendan S

•May 6, 2017

I definitely learned a lot in this course, and, as someone who has historically avoided mathematics, I think it is a fairly good introduction to these concepts for people at my level. However, I think the course was somewhat inconsistent. The final module could really use some more explanation and examples. Probability is a very abstract field, and it can be difficult to take real world examples and translate them into formulas. I think that the module would benefit greatly from spending some extra time on translating english-language situations into formulas. There were also some non-trivial errors in the videos that need to be corrected. Overall, I'm pretty happy with the course but I think it doesn't yet fill out its potential.

By F K

•Jul 26, 2020

The first two weeks of the course were well explained. But when it came to the probability, the course was confusing so that I had to search for more sources and learn from YouTube. I have been away from math for a long time, so I took this course which is described as for the beginners. I was extremely confused and disappointed about myself for not understanding the concept of Bayes Theorem for example. But when I checked other sources on YouTube, I could understand it easily and only then I was able to answer the quiz questions. So many basic concepts such as Tree diagram which are extremely helpful for grasping the theories and using them in real life situations were not even mentioned.

By Jean-Baptiste B

•Aug 24, 2020

Pretty good, overall the explanations are clear and the exercises/practice quizzes are really useful to understand the material.

Negative points: the last part on Bayes' Rule and the Binomial Theorem is a bit too fast, and I needed to supplement it by external material to fully understand it. And it would have been great to have a part about linear algebra and maybe calculus, but I guess there were some time and financial constraints that did not allow that.

I still recommend this course, that's a really good refresher or intro. You'll need to supplement it by other material, though.

By William M

•Oct 11, 2020

The positives first: Brought me up to speed on important statistics and probability information for my future career.

The not so good: The second instructor does not need to show his face. That was very distracting.

There was no working often provided in the course notes. Sometimes when I would work through a problem I would make one calculation error and couldn't easily figure out which one it was. I would prefer if they would show each calculation step by step. That would have made things a LOT faster and easier. Instead I relied to brainly, which is a great website.

By Essa

•Nov 10, 2020

I think the first two weeks were great but the probability explanations could be better. I'm sure Edgar is a great scientist but he's not very organized and the videos are very cluttered (not everyone is fit to teach just because they are in the industry). The topics covered in the probability portion of this course are better explained on free sites like Khan. I took this course to have a better understanding of the binary classification portion of the referenced specialization but don't think I gained a good understanding of the material from this course alone.

By Lucia S

•Nov 12, 2018

The course started nice and well explained, there are some useful info missing, e.g. what is Euler's constant and why is it defined as it is and then more practice examples would be also welcome. All that would be fine and I would have given the course full 5 stars, but I felt really discouraged with so many errors in the practice quizes and even in the last graded quiz. Additionally, it was a bit annoying that I could not finish the quiz on my phone as in one of the questions there was only the problem and the possible answers visible, not the question itself.

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