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

2020年5月16日

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)

AS

2019年1月11日

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)

篩選依據：

創建者 Murali M A

•2017年8月27日

Succinct explanation of the basics. Take more time at the Bayes theorem. It is worth it. Work out all the problems and keep reading the PDF notes accompanied with the videos. All in all, a great experience for those who have missed some basic math in earlier education. I am onward to my next course in machine learning and data science. Cheers

創建者 Avinaash

•2021年2月18日

I had a lot of forgotten knowledge from when i was at university which this course really helped refresh me in. I think its a really good course for a refresh or even a beginner however at times I felt a few things were too quickly glanced over when deriving formulas which made it sometime a challenge to follow but overall was a good course.

創建者 CJay

•2020年6月13日

This is a very good course for those who have forgotten about their math skills and are new to data science. The first few weeks will cover basic math which you can skim through if you are good in math. This course also introduces you to statistics in particular Bayes' theorem which is an important topic of data science. Enjoy the course!

創建者 Gitashah

•2019年1月31日

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......

創建者 Garth Z

•2017年3月10日

If you are a right-brainer and/or rusty on math, I strongly recommend this course as a precursor to Duke's Intro to Probability and Data course. Some of the practice and final quiz questions really threw me (and that's good)... Most of them I was able to rethink and derive the correct answer and a few others remain a mystery... :-)

創建者 Deleted A

•2017年1月22日

I loved this class, the only one of it's kind and much needed, unless you particularly want to re-do your long forgotten high school and college math. It was nice seeing a Venn diagram again. I did have to supplement some of the material that was covered quickly with google searches, but filling in the blanks was quick and easy.

創建者 Ramesh K

•2020年7月18日

It is a thoughtful and well-designed course. I really enjoyed learning the core math skills related to data science. As a starter on data science as a field of study and career, the course refreshed my previous knowledge and helped me learn more about the mathematical skills needed for learning and practicing data science.

創建者 Ankur A

•2018年4月18日

Hi. A very good refresher course that serves as a pre-requisite to Machine Learning and Data Science courses. Probability could have been a little better explained, specially the processes and event part. I would also like to see Vectors and Matrices added to this course, which is equally vital for Data Science.

創建者 Bernardino R

•2020年5月20日

This course provided clear, expert teaching at a very good pace. The materials were very helpful & directly applicable. The videos were well portioned, and the professors are well spoken & highly competent. I highly recommend Coursera, these professors & this course. I plan on pursuing more in this subject.

創建者 Iain S

•2021年4月4日

Everything was going fine for me until I got to the statistics portion. This is something I've struggled with before, so I can't blame the course for struggling again here, but I would have preferred more learning content for week 4, perhaps even splitting it into 2 weeks to make it a 5 week course in total.

創建者 Preeti A

•2019年1月31日

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.

創建者 Armine

•2018年4月4日

Everything was great except probability theory. The videos were hard to follow and understand because everything was a kind of mess. Reading materials would be much better for probability section. Overall it was very helpful for me and I am very grateful for this wonderful course!!!

創建者 Iman S

•2020年4月16日

The course is completely related to prerequisite data science skills. There are lots of useful materials. However, the last module (probability) is kind of introduction and superficial, and do not discuss probabilities concepts and distributions in depth.

In general, the course is Great

創建者 Olga E F C

•2021年4月14日

Fue un curso muy útil para retomar los temas de funciones y probabilidad, a mi me costó más comprender los temas de la semana 4, por lo que recomiendo busquen otros ejemplos para seguir practicando. La gran ventaja es que puedes consultar los materiales tantas veces como lo necesites.

創建者 Mahyar

•2017年8月22日

Good course because it focuses on basic statistical science needed in Data Science. Only issue I had with this course was it was pretty short. Shorter than I thought by looking at the syllabus. Also the agenda is very simple in the first couple of weeks until it gets to the last week.

創建者 Subhadip D

•2020年7月26日

Would have been better if real-time tool were used such as PTC Math-cad or Mathworks Matlab then the Simulation based learning approach could have been much better. Well this course has vas potential and can be be released as series with capstone simulation project. I loved it though

創建者 Rahul K

•2020年4月29日

very nice, this course helps me a lot for a basic understanding of the different concept of math. The course is also design in very well manner for understanding each and every concept clearly.i also very thankful to the teacher association who created this course for helping me.

創建者 Muhammed B K

•2020年10月5日

Great course for starters. For first three weeks there can be some advanced examples as extras and for the last week, it would be better if several complex examples solved by instructors since Bayes and Conditional probability can be confusing sometimes. Thanks for the course.

創建者 Rajat P T

•2020年7月20日

The course explained all the basic mathematical concepts really well, especially Bayes' theorem and probability theory.The best thing that I liked about this course is that it also explained some simple real world test scenarios where these mathematical concepts can be used.

創建者 Priti B

•2019年5月28日

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!

創建者 Pavel A

•2021年11月14日

Thank you for your work and for free access to the course. It was very helpful for my university Machine Learning course. After completing the course I want to notice the following: - course is siutable almost for evevryone - highly qualified teachers - good visual support

創建者 Adnaeva G S

•2020年10月15日

Effective way to refresh and add the Data Science math skills! Thanks a lot! Please include integration, algorithm analysis (big O, theta, omega), recursion and induction. Your course is helpful, thank you. If you add those things I've mentioned it would be absolute gold.

創建者 James T

•2018年4月2日

Everything I've tried diving into in regards to data science after having been out of school for a while (I'm 34) has been stuff I haven't learned or forgot. This course was perfect. Nothing was too difficult for someone who still remembers basic math and I learned a lot.

創建者 Josué R G S M

•2018年1月3日

Los contenidos son en inglés pero los profesores tienen una perfecta dicción y no hablan rápido de tal modo que los puedes entender perfectamente con sólo un poco de inglés. Los contenidos matemáticos están debidamente dosificados y muy interesantes. Recomiendo el curso

創建者 Aditi D

•2020年6月15日

Even though I have learnt quite a bit of math in college, my basics weren't very clear. This course helped me clear up my basic doubts which were causing problems. The instructors explain the concepts quite comprehensively using easy-to-understand real-world examples.