Вернуться к Data Science Math Skills

4.5

Оценки: 2,131

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Рецензии: 477

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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автор: 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.

автор: 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.

автор: 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.

автор: Viviana R

•Feb 19, 2019

Great course to learn basic math. It focuses on the essential and it is very clear.

автор: Mikhail G

•Mar 28, 2018

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.

автор: Danny N

•Nov 18, 2019

I thought this course was a nice refresher on basic mathematical concepts and it introduced me to set theory and probability very well! I think I am better prepared for data science afterward!

автор: Danuel R

•Apr 01, 2017

Difficult content not explained well by the presenters.

автор: Michael M

•Dec 14, 2018

amazing! i love this course

автор: Mukund B G

•Dec 04, 2018

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

автор: Harry M

•Dec 29, 2018

Thanks a lot! It's a huge important course, really... Thanks. Because I want to become a data scientist, so thanks, again.

автор: Andrey S

•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)

автор: RAJESH K

•Jan 12, 2019

I love the way teacher, teach me.

автор: Kasidis S

•Jan 04, 2019

Learned a lot from this course, thanks :)

автор: Bijan K B

•Jan 17, 2019

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

автор: K H S B

•Jan 17, 2019

Excellent course. Very detailed explanation of concepts.

автор: Kevin L

•Jan 23, 2019

Some quiz answer UI mistakes. Doesn't display the correct answer.

автор: Mai V X

•Feb 06, 2019

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

автор: robin

•Feb 19, 2019

The probability part is worth learning。

автор: 王婷婷

•Feb 19, 2019

exactly what I need. not too hard, not too hot~

автор: Kelsey G

•Feb 24, 2019

I loved the tag team between the two professors. I would love to learn more math and data science from both of them!

автор: Aftab A

•Mar 20, 2019

This course is really helpful to data science student.I was very weak in probability and statistics but this course really polish my skills.

автор: kai k

•Mar 02, 2019

it gets quite challenging at the end but its a good refresher. like the pdf helpers a ton!

автор: Lymeng C

•Mar 02, 2019

I don't quite understand the last chapter about probability. Please use more examples like in quiz to demonstrate the concept one by one. Thanks for making education free to all of us.

автор: Jonathan R

•Mar 25, 2019

Very helpful

автор: Silas M

•Mar 25, 2019

great course and good basics for anyone starting in Data science highly recommended

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