Retour à Data Science Math Skills

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1,580 avis

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)

May 06, 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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par 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.

par 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.

par 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.

par Danuel R

•Apr 01, 2017

Difficult content not explained well by the presenters.

par Austin S

•Jan 07, 2019

Silly course. Either you know so much math to be able to pass this course or you know nothing to find this course of zero value. Avoid.

par 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.

par 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)

par Jason B

•Feb 13, 2020

The first two sections of the course are well designed making it easy and clear to understand and do the practice quizzes and graded quizzes. The third section is a sign of trouble, but doable. The lack of notes giving definitions and clear formulas along with bare minimum examples in the videos make the practice and graded quizzes feel like the questions came from someone trying to trick you at every turn. By section four, it was very annoying to need to learn the concepts on Khan Academy to pass the graded test.

par Md. J R

•Jun 05, 2020

This course syllabus is great. It starts wonderfully. Week 1 to 3 is taught by Paul Bendich. His instruction is awesome. However, in week 4 Daniel Egger starts teaching log, exponential , probability which is simply a disaster. I have not seen such bad instruction in any of coursera class I have taken. I saw in Coursera he is a "top instructor" which makes me worry about coursera content as a whole. If there is a prize for how not to teach math, Daniel egger would win it.

par silvia a

•Aug 06, 2019

Dear Professor,

Please improve your handwriting. Or at least prepare your materials using slides. It will help the students understand your information better.

par Adam M R

•Apr 18, 2020

Lacked practice questions to reinforce concepts as is expected in any math course. Content in videos did not line up with assessments. Practice questions and examples would have bridged this gap. This course may function as a good refresher if you are already fairly confident in the topics but have not seen them in a while. Lecturers were very good, there was just a content mis-match between videos and assessments. Videos also contained multiple mistakes (which are noted), but should have been edited or bits re-recorded. Video editing is everywhere and accessible, there is very little excuse for not publishing a polished product considering the medium.

par Luis A C G

•May 05, 2017

I deeply regret having paid for this course. Nothing in it was oriented to data science and weeks 3 y 4 are specially weak in contents on basics on calculus and probability. Not bad if you just want to remember some things from upper secondary maths but definetly not worth to pay for it.

par Mahnaz K

•Oct 22, 2019

The course overall was great. So much math was covered that it is hard to believe it was all done in 4-5 weeks required to complete the course. It was well taught-- very relevant and clear for the most part. I have had all this math in the past so I had a frame of reference but without it I think it would be hard to follow. Having said that, I found the Probability lectures hard to follow. It seemed you need to know a lot of probability theory beforehand. Also the videos were too short in this sections and went very fast. The videos need to be 20-25 minutes with more examples. The quizzes in this section were the hardest because not many examples were given in the lecture. Overall though I feel accomplished and feel I can tackle the math that comes my way when I pursue my data science degree. Thank you for putting together a course with the background math needed for data science.

par Karl W P

•Feb 05, 2017

I graduated with a BS in computer science and mathematics 15 years ago. Since then I've been working as a Business Intelligence consultant and I've recently decided to look into the field of Data Science. I was looking for a math class to refresh my math skills rather than start from scratch and this was the perfect course for that. Kudos to Daniel Egger for creating the class. It saved my a lot of time.

par vivek d c

•May 17, 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)

par 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!

par Judy M

•Apr 27, 2020

There are a great many errors in both the lesson videos and the quizzes in this course. In the first half, correction messages pop up during the videos of the lessons. Many additional errors were highlighted over 2 years ago in the discussion forums, so it appears as though no one is currently maintaining this course at all. The second instructor does not teach content at all. He simply records on his slide what he has calculated off screen. Numbers appear in formulas but rarely is there an explanation given as to where those numbers come from or why they belong in the formula where they are substituted. Furthermore, the slides are just a jumble of notations by the end of he slide so are of no value as a reference note. Many of the discussion forum comments were suggestions by others taking the course as to where to go to get an actual lesson. Someone who did not have a background in mathematics who actually cared about learning would be very stressed by the exceptionally poor way this course is designed and delivered. Final comment -- no connections are made between the math presented and data science.

par Marcello P G d S

•May 12, 2020

First three chapters extremely simple. Last (fourth) chapter has a quiz entirely different from the contents of video lessons as well as texts.

par Omar S

•Mar 30, 2020

very beginner misleading title, not a significant knowledge in Math for DS!

par Priyanka S

•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.

par Richard S

•May 06, 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.

Thank you for a great class!!

par Gökhan T

•May 12, 2020

I understand that they wanted to explain necessary content starting gently and getting to more complex subjects gradually. But in reality they start as simple as an elementary school students finds easy. Which is not so bad. After that, complexity of the subjects may suddenly skyrocket without any explanation, even without giving necessary subjects formulas. There is assistance or further reading recommendations. No one is answering the questions on discussion forums except the students.

There are lots of other courses. This one teaches the easiest concepts in an unnecessarily long way and does "nothing" to teach complex ones which I guess why you are enrolling to this class. Shame on you Duke University. Crap course.

par geary b

•Dec 11, 2017

TRASH!

par Mario B H B

•Feb 06, 2020

Excelent course to begin!

par Simon

•Apr 15, 2020

I took this course as a refresher for maths rules I had seen in university, so my experience does not relate to those who will encounter this topics for the first time. I honestly do not recommend this course to beginners with no background in mathematics, because there is not much space given to theoretical explanations of the principles here. The course feels more like a quick slideshow of rules (logaritmic manipulations, exponential manipulations, conditional probability manipulation) followed by exercises to practice them. This is a stark contrast to my University Experience, where mathematics is about principles, logic and the demonstrations that underly theorems and their validity (e.g. ''why is the formula for combinations of "m draws on a set of n" built this way?''): deep study of these topics provides students with the mental skills to build a MODEL of whatever they come to face in real life. You may forget the rules, but those can be freshened up by a course like this. To build Logical and thinking skills instead requires a deeper understanding of mathematics and its underlying principles. I hope the professor who recorded this course will look forward to an opportunity to devise a deeper mathematics course to tackle these topics. Good luck to all fellow learners and thanks to Coursera for this opportunity!

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