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 Elena C
•A very intense course, where a lot of concepts are introduced. In order for all the new information to be metabolized, it took me much more than four weeks.
By Pedro C D
•Impressive! Very detailed in statistics and Mathematics, I would like an extensive course in logistic regression, it was short compared with lm course.
By Maxim M
•A very good course, goes deeply into the material. The pace of the professor is ok. It's nice that he uses some practical cases to explain the theory.
By Jorge B S
•I have loved this introductory course about Regression. The swirl exercises are especially useful to revise the course content and apply the theory.
By 20e
•Helpful!
If there is more introduction about the common problems people may encounter during working in the real world, the course will be better!
By Paul F G
•Excellent, highly focused course with current R libraries for learning various regression methods and methodology. I highly recommend this course.
By Juliusz G
•Very practical/hands-on intro to regression models. You will definitely be able to apply those methods after this course whenever you need them.
By Hernan D S P
•This course is perfect to get started with Regression Models in R! I think you would need some familiarity with the statistical concept though.
By Reza M
•Excellent course on regression modelling it showcases the power of R. quite a heavy module though for people with none statistical background
By Kumar G G
•I think this is the best course I have ever came across in the coursera. Everything is discussed in the most simple manner with great depth.
By Shivendra S
•In-depth and detailed, this one month course will provide aspirants with the knowledge and skills required to conduct efficient regressions.
By Lopamudra S
•The Regression Models is an excellent course for a beginner.I would recommend the enthusiastic students for a great start in Data science.
By Emanuele M
•It's a great course and tought very well. It required effort, you apply many of previously teach concept and requires a lot of excercise
By Abhinav G
•Very Helpful course. I am from a non -stats background and this has helped me a lot in understanding such deep concepts of Statistics.
By MEKIE Y R K
•Really interesting and full of advices.
But would like to dig more into the Logistic and poisson regression residuals explanations :)
By Matthew C
•Week 4 was a lot harder than the other weeks (specifically the quiz). Overall, a lot of great information packed into this month.
By Sandra M
•Everything you need to know to have a clear understanding of regression models and learn how to use their basic functions in R.
By Damien C
•Great ressources. Usefull presentations, maybe too rich for a newbie.
It was too fast for me. Could be done in 2x more time :/
By Richard F
•This is the most challenging course so far - new concepts, new approaches and application to a wide variety of situations.
By Connor B
•Learned a lot and enjoyed the course project. Would like to have two course projects because I gain the most out of them.
By Carlos B
•Thank you for the chance to review all the fundamental and applied mathematical and statistical aspects of data analysis.
By Stefan S
•Not the easiest course, but very rewarding if you hang in there. The material is very well explained with ample examples.
By Nino P
•Similarly to statistical inference, this is a bit harder course in the specialization. Still passable and recommendable.
By Rafael M
•Excelente curso, requiere de esfuerzo y dedicación, ademas de una solida base estadística. Práctico y de mucha utilidad.
By Vitor P B
•Very detailed and complete course with heavy theorical concepts which are all very useful for data science applications