(44 Reviews)
SM
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.
ES
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 Carlos A H
鈥Jul 1, 2019
Excellent overview of implementing practical data science; however, an area of improvement is emphasizing machine learning as a practical solution for finding answers especially with large and complex data sets.
By JOHN W E
鈥Apr 29, 2020
Brian is an amazing teacher. He just miniaturized the basics of data science in a week and I could still understand better all the necessities of it, Thank you for making such a course. I highly appreciate it.
By ARVIND S
鈥Jun 4, 2020
Exceptional course in conveying a real life situation, vastly different from an ideal one. The course puts you up to speed in handling such situations with aplomb.
By Elitza K
鈥May 5, 2021
well structured, very clear and vital examples; extremely useful and practical recommendations. I've enjoyed the course and have learned a lot of short time!
By Manjunatha V M
鈥Jan 8, 2017
Clear explanation of various concepts with good examples. Of course, reference to some cool cartoons from time to time made the concepts more memorable!
By Carlos J
鈥Sep 20, 2017
Esta serie de cursos, es recomendable para iniciar en la carrera de Ciencia de Datos, conceptos claros, expuestos por catedr谩ticos de primer nivel
By Alfredo O G
鈥Nov 14, 2016
An amazing course for those who are not very familiar with statistics and a very refreshing perspective for those who actually knows statistics!
By Gurpreet K K
鈥Aug 2, 2021
The lecturer has obvisously been through all the issues and learnt about them, perhaps first hand. It was a delight! Thanks so much!
By Edgar A C V
鈥May 15, 2018
I just finished this course but I cant enroll to the last one (I have 4/5 course in this moment). Can you please help me?? thanks!!!
By Gautam R
鈥May 17, 2020
Wanted some practical examples - of calculating P values with sample set of data & analyzing/reporting on it with inference.
By Emmanuelle M
鈥Oct 11, 2018
Great course, although, if you are not already working or have knowledge in this particular filed/topic, it is challenging.
By Michael L
鈥Apr 1, 2018
An excellent overview of the topic material without a lot of unnecessary clutter. Well-organized and -communicated. Kudos.
By Paulo B S
鈥Jul 8, 2019
The authors really present real situation and challenges that data scientists face in their daily activities. Very good.
By Roque A
鈥Sep 24, 2018
Very easy to follow with good examples. The focus on this course was on practicality and I really appreciated that
By Victor D R L
鈥May 30, 2020
This is a very good course but challeging. There is just too many concepts, recommendations and ideas to tackle.
By William K
鈥Jan 4, 2017
Excellent course. The material is good enough that will help me where to look for information, considerations, a
By Alberto D E
鈥May 14, 2018
A crash course on what can go wrong in real Data Science projects, and how to improve your chances of success.
By Ryan S
鈥Nov 11, 2019
I found this course to be the most enjoyable and knowledge benefiting of all the courses I've taken thus far.
By Elton K
鈥Dec 14, 2018
Interesting for a Non-Data Science Executive despite some minor spelling errors in video transcripts.
By Matthias L
鈥Aug 28, 2017
This is very useful and a good primer on what to look out for when working in real life. Well done!
By Sambit K D
鈥Dec 8, 2020
The instructor Brian Caffo is very knowledgeable and great presenter. Has real practical examples.
By Bart P
鈥Apr 13, 2019
Very useful course! I really enjoyed the technical not so much the statistical part of the course.
By Paul S
鈥Jan 28, 2017
Helpful tips for handling problems during the several life cycle stages of a Data Science project.
By Mauricio L
鈥Jun 22, 2019
Great course. It delivers a fantastic framework to assess the process of successful Data Science.
By Ayna M
鈥Dec 14, 2017
Loved all the examples to explain the terms like confounding, blocking, surrogate variables etc.