25 oct. 2018
Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .
24 sept. 2020
the teachers were awesome in this course. I liked this course a lot.Understood it properly.Thanks to all the beloved teachers and mentors who toiled hard to make these course easy to handle.Gracious!
par Charles K•
18 sept. 2016
The instructors approach in this course is very cursory. He tries to split the difference in going through the mechanics/mathematical theory and practical applications. As a result, he fails at both. I think it would be better to leave the mathematics and application learning to supporting materials and focus on explaining the theory and concepts of statistical inference in the lectures.
par Thej K•
14 avr. 2019
The hardest course I have ever taken! Very hard to follow! Spent a lot of time, trying to understnad the lectures! The final assignment was really good, it really tied everything together! But the lectures and following them was a nightmare and hard to understand! I spent 55 hrs on this particular course! and the last week 4 I spent 20 hrs on this course
par Rajit A•
2 avr. 2019
The course is very technical and needs a) reading and practice outside of the material presented here and, b) needs you to invest a lot more time than you might believe before you start this course. So if you are looking to just understand the basics of statistical inference or if you don't have a background in statistics then this is best avoided.
par Jake T T•
8 avr. 2018
This was a difficult course to get through. The lectures were almost completely useless - I had to look up videos from youtube and other sources for every single lecture to learn the concept, and then rewatch the lecture - even then the instructor was difficult to follow. If this wasn't part of the specialization I would have dropped the course.
par Eugene K•
8 mars 2018
Good material but the lectures are not well put together for the novice. I think the professor needs to have a little more empathy for the students and not just read notes for the class. Too many sentences with esoteric terms are spewed out without truly trying to explain the material in a way that the student will understand.
par Omer A•
15 mai 2016
this is heavy material, and I suggest it be broken down to two separate courses, and the author take his time in explaining the various concepts in much more detail vs. trying to cram them within 5 or 10 minute sessions. I know I wasn't the only one struggling to keep up with the teacher after week 2.
par Stephane B•
11 avr. 2018
The content of this course is interesting and i learned a lot BUT it's indeed badly explained, and i lost a lot of time to understand certain things. My advice: watch others videos (from Khan Academy for instance) in order to understand the basics concepts and then, come back to this course.
par Patrick S•
9 févr. 2017
Sorry to say, but for me as a non-native english speaker, most videos are hard to follow. Its because speaker talks fast, unclean and with bad sound quality. Of course I'm not used to the mathematical english terms. Also the many animations with the slides made it hard for me.
par Craig G•
26 juil. 2017
It may be that this is the first Math heavy course in the data science specialisation, but I found this one really hard going, with the videos being particularly hard to follow. I had to do a lot of extra research to find alternative explanations of the concepts involved
par Alex B•
29 déc. 2018
Doesn't really teach you stats, gives you a rough idea but only shows you that it's possible in R. Doesn't really explain what it's doing or how to do it, rather "here's a handy R function that does this". Meaning I'm just learning R rather than any actual stats.
par Mourad Y•
26 nov. 2017
True the content is rich, but the instructor is not engaging and much content is not well explained so the learner should search everywhere. If it is to compare with khan academy videos for example, they are much more coherent and way too easier to understand
par Arjun S•
17 sept. 2017
To someone new to statistics, this course does NOT help. The professor does not seem too interested or enthusiastic and seems like he is reading off the slides. Concepts are not explained clearly at all. Forced myself through this course :(
par Rui P•
10 oct. 2016
Despite the pertinent content, the way the instructor gave the classes could have been way more intuitive. You'll find videos on the web that can help you with the subjects covered and do a better job explaining the concepts. Disappointing.
par Chandrakanth K•
5 nov. 2017
Some concepts are advanced and it requires detailed knowledge of statistics. It would be good to add a chapter to explain the basics before going through advanced concepts. The explanation in some of chapters are very basic.
par Tanguy L•
25 févr. 2017
This course should not be presented by video. I loose lot of time by learn with others supports than Coursera.
Even if I notice and appreciate the works to produce these supports by the teacher, I'm not a big fan at all.
par Manny R•
29 déc. 2018
this is a difficult subject that takes a lot of practice to understand. would like to see the course time and materials extended. It would also be helpful to have live online sessions with instructor and classmates.
par Karishma A•
21 mars 2018
I think the course was very informative but it took me about 3 months to finish course. Lot of important concepts have been condensed to one or two slides which makes it really hard to grasp the concept quickly.
par BAUYRJAN J•
27 nov. 2016
This course is great, but Brian is certainly not a good instructor. He does not explain things well, and articulate examples. I had to take Statistical Inference from Duke university to pass this course.
par Devashish S•
14 oct. 2016
This course is poorly taught. The instructors often speed through significant concepts and are generally unable to explain the concepts clearly to someone who does not have a major statistics background.
par Jennifer D•
3 mars 2016
Taught very quickly and assumes a high degree of math fluency. Only take this if you are either very fluent in math already or have a significant amount of time to devote to understanding the material.
par Louis T•
29 janv. 2022
Very confusing instructor and unstructured course, prior knowledge of covered topics is definetely required to fo through the course. Additional reading helps to solidify the knowledge.
13 juin 2016
Very poor instruction and organization of topics, very poor explanation of core concepts. I learned more from reading other sources while taking the class than I did from the lectures.
par yohan A H•
10 juil. 2019
The topics are very interesting and there is no dude that the teacher knows wath he is teaching, even though I think it can be better with more grapics splanations and less formulas.
par marie s•
5 juil. 2017
A lot of the course were not explained in a way that made it easy to understand for a neophyte. I had to go re-watch most of the lessons on khan academy to understand the principles.
par Luis F F•
13 déc. 2020
I feel that I need a more detailed approach regarding the statistical information. The course covers a broad range of topics but the approach seems a littile advanced.