Back to Data Science Math Skills

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9,146 ratings

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2,072 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!...

VS

Sep 22, 2020

This course syllabus is great. It starts wonderfully. Week 1 to 4 is taught by Paul Bendich, and Daniel Egger the instruction is awesome. Effective way to refresh and add the Data Science math skills!

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 Aydar A

•Aug 28, 2017

too superficial to be usefull

By Prasad K

•Jan 11, 2019

1st 2 weeks were very basic.

By Vijay G

•Jul 12, 2020

Great mathematical analysis

By Snigdha G

•Oct 13, 2020

Can I get a Certificate?

By Hugh J

•Sep 27, 2020

Needs more statistics

By Elvin G

•Oct 19, 2018

It is too low level

By Korkrid A

•Apr 27, 2018

Good for beginners.

By Vikas G

•Jun 17, 2020

Fantastic teaching

By PARDESHI R H

•May 17, 2020

Very useful course

By Shanmuga P

•Feb 23, 2018

Good!!

By MUTHU A P S

•Jun 7, 2020

good

By Carolin K S

•Jul 21, 2020

This class fails to give a single explanation as to how the math skills will apply to data science. The first three weeks are a nice basic explanation of some of the math that will be needed. If you haven't done coding before or have some background in coding, you will have no idea where this class is going to be applied. The fourth week is the worst explanation of probability you can imagine -- opaque derivations and almost no explanations. I do not recommend this class as it fails to address the "why" of the title -- how does math apply to data science.

By Mike S

•Mar 18, 2021

The content is OK; the execution isn't quite ready. Most is fairly basic, but is necessary and potentially a good review. But the course comes across like a first draft. Mistakes in videos are not re-recorded, but called out with a disclaimer. I believe there are two errors in answers to practices and quizzes, but it's possibly my own mistake on one. I noticed one instance where the correct answer is in a different font than incorrect answers. Overall, OK content but not very polished. It could use a second revision.

By Borja C

•Sep 10, 2020

The first 3 weeks are quite good... but then it makes a gigantic leap on the 4th week. Please update the explanations on Bayes and the examples... they are not optimal. Judging from the comments I have seen, I am not the only one.

Thinking about it, I think maybe it would be worth to spend more time with probability and a bit less with the other stuff or even add another week... definitely probability in one week is a far shot... and it is key to understand data science correctly

By Helene H

•Sep 25, 2020

A pretty good course even if week 3 and 4 are very difficult for beginners.

A few improvements are urgently needed:

-There are mistakes in the quizzes, which mistakes have been pointed out by generations of students for months/years in the forums, but have never been corrected. Such a disgrace and waste of student time!

-Also using Chrome makes you unable to read the formulas, which should be said in the course outset.

By Deepak R

•Dec 27, 2020

At week 4 the course was covered in a rush. This course could have been much better if the instructor could have taken the time out and walked the extra mile to simplify the concepts for a larger audience. I already had previous rigorous treatment of Probability theory hence didn't face many challenges. But I have empathy with students enrolling in this course who don't have prior probability background.

By Yury K

•Jul 14, 2020

Course has misleading title. It has no strong connection to data science problems or examples from the field (except confussion matrix). First 3 weeks are simple math. Third one is very brief tour to probability with quite brief explanations which will not be enough for beginners to complete the assignment. There are also errors in the asssigments which I had reported.

I will not recommend it.

By Joel L

•Sep 8, 2020

Instructors were knowledgeable, but I found the lectures to be a theoretical example, followed by a very simple real-life example. Then when you take the quiz, the questions are SIGNIFICANTLY more complicated than what I was ever taught in the lessons. Some worksheets of sample problems that escalate up to the difficulties seen in the quiz would have been very helpful.

By Utsav S

•May 6, 2020

The course content was very basic. Especially the first part of the course.

The later part(probability) of the course was very theoretical in nature. Typical problems in quizzes and examples as you would find in any mathematics text book. Being Data Science Maths skills course, I was expecting some real life example or even the mention of data science during the course.

By Esdras C

•Mar 6, 2020

After the second week, explanations become too abstract without a concrete explanation of how relates with the real world. Also, the examples are too short compare to the problems that are included in the quizzes. It will be way more interesting to learn the explanation of the quizzes than the abstract examples during the presentations.

By John

•Jul 22, 2020

Some useful concepts, but several of them, especially in the last week of the course, were very vague and did not give examples on how to use them to solve problems, which is the point of the course. If i wanted definitions and formulas I can just google them. The whole point of a video is to teach me how to apply it

By Syed S W

•May 21, 2020

The initial modules are insightful and helpful. But I had a lot of problems going through the material in week 4. The instructor struggles to make the content engaging and the videos often end up sounding very monotone. There's a big gap between the material discussed and the questions asked in practice.

By Jansen M A

•Dec 31, 2020

The course is fairly easy and unchallenging. It's like an introduction in maths for high school students. I was expecting harder maths related to data science and/or machine learning, but this is just a review of high school maths. Not entirely a waste of time, but disappointing.

By Tanmay A

•May 28, 2020

baye's theorem and the binomial addition to it should have been explained broadly, this is a multi country based program , people from different country access it. hence each and every formulae and colocations should be explained better and write-in a better way.

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