Back to Data Science Math Skills

stars

9,593 ratings

•

2,179 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!...

AS

Jan 11, 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)

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!!

Filter by:

By Elizabeth C

•Jan 14, 2021

Didn't like it. It helped me cover some of the concepts I have to know as an aspiring data scientist and the problems are good though tricky, but the explanations were confusing. I often find myself watching Khan Academy videos then coming back to do the questions.

By Aasiya S

•Jul 28, 2021

The course could have been better, since majority concepts were not explained elaborately especially module 4. Will not recommend if you really want to learn something. Tests and assignments were good as they were not direct questions but based on application.

By Taruna J

•Aug 6, 2020

Some concepts have been explained beautifully, which made things easier to understand. Some concepts (probability) I earlier understood so very well, but now I am confused with the teachings from this course. I don't really like how it has been explained.

By Nitikorn S

•May 22, 2020

The first half is really well explained. However, the second part could be improved with a more detailed explanation rather than introducing the equation and jump straight to the problem. Also, I think the quizzes in the latter part are (too) difficult.

By KRISHNAMURTHI R

•May 22, 2020

Concepts are not clearly explained in the video sessions. I had to seek some other you tube videos to get the concepts with clarity . Some of the Practice quiz feedback are not fully explanatory and required more outside reference to clear the doubts .

By Sahar A

•Dec 31, 2020

It was a good review for me. However, I expected the course curriculum to be more advanced, considering the course title. It was mostly some basics. But good if you want to have a review on some probability subjects that you may have forgotten.

By Chris

•Nov 8, 2019

You guys need to give better practice examples and scenarios in Weeks 3 and 4. That being said, I think the courses you presented give a nice foundation. I'm going to practice on my own time finding problems of the subjects you've spoken about.

By Gregory B

•May 5, 2020

The course has issues later on - there is inconsistent notation, no provided worksheets, formula sheets, documentation, or summaries of any kind. At first this isn't a problem when the course is simple but is much more problematic later on.

By Saeed M

•Sep 2, 2020

As a whole: very useful review of the themes.

However:

Quite a few Latex statements spread around the quizes.

Probability could be explained a bit more thoroughly. I had to look up external sources to get a better grasp of the subject matter.

By Andre G

•Jan 13, 2021

Sometimes a little bit confusing due to the handwritings. In addition I would not expect a wrong statements/mistake in 10 minute video, sure the corrections are fine, but I would recommend to record the video again without any mistakes.

By Celtikill

•Oct 11, 2020

Challenging module which lacks the practical application needed to feel confident going into quizzes. I found working through the quizzes themselves more valuable than the reading material. Plan to watch, rewatch, and take good notes.

By Georgina M

•Aug 2, 2020

Some really good course content, but a strange mix of levels/difficulty. I have some maths background so skipped most of the videos but using the notes and quizzes I still learned some new topics (like set notation and Bayes theorem).

By sudip t

•Jul 12, 2020

It was nothing new and easy for me but if you have a gap in your study and forgot whatever you had studied in your school then this course is definitely for you to learn some math skills which is important for data science.

By Andrea P

•Dec 22, 2017

A good review of basic math skills, however I believed the "SUM RULE, CONDITIONAL PROBABILITY AND BAYES'THEOREM should be discussed much more in the last week module with more example and exercise. The 1,2,3 week are great.

By MJ A

•Jul 12, 2020

The first 2 parts(weeks) were good and easy to grasp, but the last two were a bit advanced and needed more time to handle the concepts, but overall a good course in general, get more more practice before attempting quiz

By Bobby M

•Jul 19, 2020

The early videos are good. The videos toward the end were not as helpful for a person new to the subject. I had to look up other tutorials on youtube to understand the material enough to pass the quiz and final test.

By Michael L

•Oct 18, 2017

I feel the probability portion of the course was too quick for the material covered. Yet the quizzes for the probability section were very demanding. It was difficult to successfully complete the probability quizzes.

By Jason C

•Aug 3, 2020

The class starts off very well. When it moves to the full professor, the lesson quality falls, as the lectures lack the younger professor's examples and explanations which guided the learner into the quiz material.

By Siyabonga F C

•Feb 3, 2021

Had trouble with week four, I think the instructor tried to summarize Bayes theorem, but it made it vague, had to watch other videos from other sources to fully understand the concept. Otherwise it was good.

By theo

•Apr 24, 2020

The first three weeks are well explained, the last week is the most difficult and the professor does not provide examples. There are many mistakes in the quizzes and this seems to be done very haphazardly.

By 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.

By Supasuk L

•Aug 9, 2020

The part about baye's theprem is really hard to grasp, perhaps less equation and more diagram would be better for student to understand the concept. (for me I look at youtube for better understanding)

By vignaux

•Nov 2, 2020

The course is well but the last part of the course is boring because the principal interest of the course is data analyst with explanation of smart theorem as Baye's and this is not very well explain

By Karen B

•Mar 25, 2021

The first sections are very good. Nice review and learned some new concepts (or at least was a refresh). The probability section is a tad weak. Could use more explanation and more examples.

By Patricia C

•Jan 26, 2021

Good basic review, but I would have liked more examples. (Examples did not have to be in video format, but perhaps in supplementary material.) Very much appreciated that this was offered.

- Google Data Analyst
- Google Project Management
- Google UX Design
- Google IT Support
- IBM Data Science
- IBM Data Analyst
- IBM Data Analytics with Excel and R
- IBM Cybersecurity Analyst
- Facebook Social Media Marketing
- IBM Full Stack Cloud Developer
- Salesforce Sales Development Representative
- Salesforce Sales Operations
- Soporte de Tecnologías de la Información de Google
- Certificado profesional de Suporte em TI do Google
- Google IT Automation with Python
- DeepLearning.AI Tensorflow
- Popular Cybersecurity Certifications
- Popular SQL Certifications
- Popular IT Certifications
- See all certificates

- Skills for Data Science Teams
- Data Driven Decision Making
- Software Engineering Skills
- Soft Skills for Engineering Teams
- Management Skills
- Marketing Skills
- Skills for Sales Teams
- Product Manager Skills
- Skills for Finance
- Android Development Projects
- TensorFlow and Keras Projects
- Python for Everybody
- Deep Learning
- Excel Skills for Business
- Business Foundations
- Machine Learning
- AWS Fundamentals
- Data Engineering Foundations
- Data Analyst Skills
- Skills for UX Designers

- MasterTrack® Certificates
- Professional Certificates
- University Certificates
- MBA & Business Degrees
- Data Science Degrees
- Computer Science Degrees
- Data Analytics Degrees
- Public Health Degrees
- Social Sciences Degrees
- Management Degrees
- Degrees from Top European Universities
- Master's Degrees
- Bachelor's Degrees
- Degrees with a Performance Pathway
- Bsc Courses
- What is a Bachelor's Degree?
- How Long Does a Master's Degree Take?
- Is an Online MBA Worth It?
- 7 Ways to Pay for Graduate School
- See all degrees