Avis et commentaires pour d'étudiants pour Data Science Math Skills par Université Duke
À propos du cours
Meilleurs avis
AS
11 janv. 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)
VS
22 sept. 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!
2051 - 2075 sur 2,332 Avis pour Data Science Math Skills
par Paurush K
•4 mai 2020
great
par Prashant M K
•9 déc. 2020
good
par Prerna S
•10 juil. 2020
good
par Nagraj t
•6 juil. 2020
good
par Nishant S
•4 juil. 2020
nice
par Perumali S
•27 juin 2020
good
par LIJIN W
•16 juin 2020
Nice
par AVINASH K
•8 juin 2020
Nice
par Labib U
•7 juin 2020
good
par AVALA S
•2 juin 2020
Good
par Sunil R
•1 juin 2020
Gooo
par Mitesh M
•13 mai 2020
good
par TEJASWINI D
•7 mai 2020
GOOD
par Prateek G
•4 mai 2020
good
par SREERAM S
•10 avr. 2020
good
par Abanoub S M
•8 nov. 2021
4
par Fariha A S
•1 sept. 2021
4
par Sakshi B
•21 juil. 2021
i
par Jay Y
•7 mai 2020
.
par Amin A
•4 sept. 2019
.
par Nagaraj A M
•9 mai 2019
.
par nikhil k
•15 févr. 2021
well the initial part of the course is very basic .. too basic.. the course doesn't scale up with the first 3 weeks. but the instructor is clear and makes concept easy to understand. but things change in the fourth week. the course shifts gears from very easy to intermediate. without much guidance.. or examples
math skills are to be practiced i hope the instructors level out the difficulty level in the course. An ideal math course should have many examples to practice with constant involvement of the instructors , support guys.
just 5 or 10 problems doesn't get you much and when asked to pass with 80% is tough.
. i left the course in week 4 and again completed after i understood week 4 content better.
this course doesn't have many many of the math skills required for data science.
ideally a math course should scale up from simple easy to intermediate to hard and later challenging questions and final assignment should have a combination of first 3 and passing of 70 to 75..
so the course requires
a. more examples for practice with solutions atleast 20 -25 both solved and unsolved
b. more math topics to make it more comprehensive for data science
c. more involvement overall
par Brendan S
•6 mai 2017
I definitely learned a lot in this course, and, as someone who has historically avoided mathematics, I think it is a fairly good introduction to these concepts for people at my level. However, I think the course was somewhat inconsistent. The final module could really use some more explanation and examples. Probability is a very abstract field, and it can be difficult to take real world examples and translate them into formulas. I think that the module would benefit greatly from spending some extra time on translating english-language situations into formulas. There were also some non-trivial errors in the videos that need to be corrected. Overall, I'm pretty happy with the course but I think it doesn't yet fill out its potential.
par F K
•26 juil. 2020
The first two weeks of the course were well explained. But when it came to the probability, the course was confusing so that I had to search for more sources and learn from YouTube. I have been away from math for a long time, so I took this course which is described as for the beginners. I was extremely confused and disappointed about myself for not understanding the concept of Bayes Theorem for example. But when I checked other sources on YouTube, I could understand it easily and only then I was able to answer the quiz questions. So many basic concepts such as Tree diagram which are extremely helpful for grasping the theories and using them in real life situations were not even mentioned.
par Jean-Baptiste B
•24 août 2020
Pretty good, overall the explanations are clear and the exercises/practice quizzes are really useful to understand the material.
Negative points: the last part on Bayes' Rule and the Binomial Theorem is a bit too fast, and I needed to supplement it by external material to fully understand it. And it would have been great to have a part about linear algebra and maybe calculus, but I guess there were some time and financial constraints that did not allow that.
I still recommend this course, that's a really good refresher or intro. You'll need to supplement it by other material, though.
Coursera Footer
