Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.
It really helped me to have a better understanding of these Regression Models. However, I've noticed that there is a video recording repeated: Week 3, Model Selection. Part 3 is included in Part 2.
By Humberto R•
Great course. My prefered so far in the data science specialization
By Mingda W•
Great, but need more examples and projects to practice the skills.
By antonio q•
to me the more challenging course, well done though, thanks a lot
By Hariharan D•
Intuitive course, liked it. Technical equations are challenging.
sufficient depth but explnation is not sufficient in many places
By Piotr K•
Sometimes videos were hard to understand, especially in week 3.
By Frank O•
Mathematically difficult topic for me, but very well conveyed
By Alexandros A•
I expected more in Binomial Regression and Poisson regression
By Yiyang Z•
Very informative, but could be more interesting and concise.
By Manuel E•
Hard class, documentation could be better, but good content.
By Alzum S M•
Very much thank you for teaching me such an awesome course
By Pooia L•
This is a very nice course provided you study a lot for it
By Karthik R•
Knowledge on Statistics will help in better understanding.
By Luong M Q•
some complicated contents that are hard to fully grasp.
By H Y•
Content regarding variable selection is kind of rough.
By Camilo Y•
Great introduction to regression models. Pretty clear
prerequisites are very mandatory to do this course
By pulkit k•
It lacked practical application, not impressed.
By Mitraputra G•
A little monotonous sometimes. Otherwise good.
By Mehrshad E•
I found SWIRL more helpful than the lectures.
By Sameen S•
The lectures were a bit complex and lengthy.
By Ankush K•
really informative with helpful examples.
By Mehul P•
Easy way to understand Regression.
By David E L B•
Really helpful and well presented.
Advance topic in regression model.