Jun 28, 2018
The professor is really enthusiasm, so I was really impreesed by him. And his teaching is brief, and I can learn key points through the lectures. Great course!
May 23, 2016
I have really enjoyed the course and I have learnt different concepts relevant for my current study.\n\nYurany
par sandeep s•
Dec 20, 2016
The course was tough and was explained in a very fast way assuming that the student knows prior statistics.
par John M•
May 25, 2017
Covers a large amount of material in a short time.
You will learn a lot but you will have to spend a lot of time researching and experimenting.
par Thodoris S•
May 23, 2018
too much overlap with Jeff's course in introduction to genomic data science
par David B•
Feb 24, 2019
Theory part, remaining that it has to be done in pills, could be done a lot better. R part is done better, but the principal issue is that you have not a clear connection with theory.
par Matt C•
Jun 27, 2017
For some reason, this was a really tough course, it blew my socks off. I did not get the explanations they just did not sink in.
par Gonzalo C S•
Apr 04, 2017
Bad or superficial explanations. The instructor speaks very fast and you need to continually stop the video to keep the pace. Some interesting commands and are shown, but the instructor seems to be tired of explaining them and defers explanations to lots of links at the end of each video.
par Paul S•
Jan 03, 2018
The worst executed course I have taken in 36 years of post-graduate education.
1 The instructor speaks so fast it is difficult even for a native English speaker like myself to understand.
2. This course is only suitable as a review for people who are experts in the field already. Even if you know how to use Bioconductor and are familiar with programming in R, if you don't know the tools being used already the instruction in the course will not give enough information to be able to do the quizzes without a great deal of difficulty.
3. The examples presented are thrown out in a cursory fashion without enough detail about how the data is being set up or manipulated. Matrices are transformed and recombined with little explanation about why things are being done.
4. Although generalizing from material presented to new applications is a valid instructional approach, the instruction does not give the student enough information to do this and the instructor expects students to be able to figure out new algorithms from vague public domain documentation.
5. Although the instructor makes an impassioned plea for carefully thought out statistical test design, proper documentation of work flow, and appropriate use of p-values, he does not describe the interpretation of statistical tools presented. For example, tools for calculating thousands of principle components in seconds is given, but beyond showing clusters of dots on a graph may indicate a genetic cluster does not explain what the individual points in the PCA mean.
In summary, the tools presented are very powerful but are not well described. Extensive revision to the course is needed.
par Andrew M•
Oct 29, 2017
This course is the shotgun approach to this topic. There's way too much material covered so shallowly that the instructor may as well not have bothered. While it is true that the course is heavily annotated with web links and references, IMNSHO, this is a cop-out. This course could improve dramatically by extending it a couple of weeks and covering some of the material in greater depth. I think the instructor also also buried his lede by deferring the discussion of predictive statistics and an overview various experimental processes/software until week 4. Both of these topics deserve better treatment front and center in week 1.