Aug 20, 2017
A very good and concise course that helps to understand the basics of the Data Science and its applications. The examples are very relevant and helps to understand the topic easily.
Nov 12, 2017
Highly educational course on the realities of data analysis. Many good tips for your own analyses as well as for managing others responsible for coherent and accurate analyses.
By Robert A•
Feb 04, 2016
Brian, Jeff, and Roger: Thank you very much for all the data science courses, really great. I generally rate them 5 stars. But for this one, I'm giving 3 stars, not because the content is not good (it is; it provides good practical and experiential information), but rather because the material seems repetitive at times either within the same course or with topics in the other courses. Also, the sequencing and lectures seem sometime a bit disjointed.
May I humbly suggest an idea: Integrate the key points of this course relating to real-world examples and the sharing of real-world experiences into one of the other courses.
Robert Al-Jaar, PhD
By Ruben S•
Aug 17, 2016
Brian tries to achieve too much in too little time. It addresses important issues and it gives a good overview, including some hidden gems (Machine Learning vs Stats, for example), but it feels mostly too rushed and superficial for my taste/expectations, and it fails to connect to my previous knowledge (and I have a PhD in Maths, although no strong Stats background), hence little added value for me when I cannot relate to what is being discussed.
By Rajeev R•
Dec 07, 2015
Lectures themselves were OK, but presentation needs work. Intro session was very repetitive. Lot of jargon introduced without explanation. Pop-ups w text showed up but disappeared before I was able to finish reading them. Best part of course was actually the text notes at the beginning of each sesssion. A minor nitpick: course description suggests that there are 3 instructors presenting, but I only saw one.
By Gonzalo G A•
Dec 16, 2016
It's sometimes difficult to follow professors beacuse they take for granted information about the examples they use that is not evident for the learners. They should take a minute to explain a little bit more what the examples consist of and what are the charts they show. As it happens when Brian Caffo explains the blocking adjustments part.
By Cauri J•
Jul 04, 2017
I found this course used a lot of jargon without explanation. It seems like the instructor understands the content so well that he assumes a level of knowledge from students that do not match the expectations of the rest of the content in this track. At the same time I found the content well presented.
By Michail C•
Jul 17, 2019
This course is an excellent effort to document the issues faced in real-life data science. However, the flow of the videos seems to be a bit confusing and some of the content is explained in a weird manner.
By Daniel C d F•
Dec 06, 2016
I missed several concepts to better understand some of the discussions and explanations. It was valid, but I think the statistics background should be better explored.
By Peter L•
Aug 14, 2018
The course is valuable but highly focussed on scientific applications (inference) and less on business application (i.e. prediction). I hoped for a more even mix.
By Sean H•
Nov 24, 2015
The video quality and content were good. Unfortunately, there were a lot of spelling errors and grammatical mistakes in the written portions.
By Chong K M•
Mar 18, 2018
Very difficult and time consuming course which contains a lot of technical words and jargon. Not recommended for the average beginner.
By Jean-Michel M•
Feb 22, 2019
I would drop some of the cartoons. They are funny but they seem to distract Bryan and overall it's distracting for us students too.
By Rong-Rong C•
Dec 14, 2017
There is a lot of technical jargon covered which made the course more challenging than the other courses in the series.
By Alberto M B•
Mar 20, 2019
It wasn't as focus on Managing Data Scientists as I was expecting, but rather focus on tips for Data Scientist.
By Marco A P•
Jan 03, 2017
Much theorical with few examples. Could incorporate examples outside the health world as well.
By Gilson F•
Aug 02, 2019
Não gostei muito da didatica do instrutor e os slides não ajudam no entendimento
By emilio z•
Jun 06, 2017
Explanations in videos qere not very clear nor very well connecetd with the Quiz
By Christopher L•
May 03, 2018
Would have liked a bit more examples and math in some cases. Others were fine.
By Ioannis L•
Apr 09, 2017
A bit less engaging than the other parts of the Executive Data Science course.
By Patricia S•
Jan 02, 2020
good content but could be simplified and presented in a more focused man
By Amal L C•
Mar 16, 2017
It was quite hard with all the statistical jargon. Too much theory.
By Poon F•
Jan 30, 2018
This class has more useful materials than previous ones.
By Manas B•
May 11, 2016
Relevant materials, but lecture delivery is rather dry,
By Matej K•
May 01, 2018
Sometimes it was hard to understand what's going on.
Apr 02, 2019
The material is too long and boring.
By Weihua W•
Jan 19, 2016
Too short, too expensive.