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.
por Pedro J•
The professor doesn't explain clearly as part of the videos is his correcting himself or saying the same thing two or three times. And why must the videos show the teacher? It distracts from the slides and seeing him move doesn't help understand anything better
Concepts like VIF or hat values are not very well explained by the teacher, at least the SWIRL lesson explains it correctly. ANOVA and ANCOVA are mentioned in the description but they aren't explained anywhere. ANOVA is used without any explanation of what it is.
I found myself searching online for other sources to understand the concepts.
por Lee D•
I again found many of the lectures to be difficult to follow along, there seems to be lots of different styles of videos in the way that the person was superimposed on the slides. In fact it was often impossible to read the text in the slide due to the size of the presenters head which obscured the text. Honestly this data science course is getting worse as the months progress, you really should think of updating the content of the course if you want to continue to charge money for it. 2 stars as I did actually learn something despite the quality of the material and its delivery.
por B C•
Overall okay course but the lectures are too focused on theory with some applications to the real world. I think this course needs to be reconfigured and taught from an applied focus instead of 30% applied 70% theory.
Also the new format is horrible and TAs are nonexistent as are discussions in general on the forums now. The TAs were a critical learning component before especially considering that unlike on EdX where course staff actually participates in the forums, on Coursera I do not think I have ever observed course staff actively participating in the forums.
por simon m•
The concepts behind this course are really important. However, I feel that the material is not up to the needed level.
I am missing a good solid material that explains properly the theory behind these methods. I had to revert to other books (that could have well showed up as references in the course material) to get a proper understanding.
por Thej K•
Worst teaching by Brian Caffo! typos in quizes after 4 years even. And brian has put very littel effort into making it digestable for students. Look at his lectures on youtube and I have commented at each lecture! So bad. A simple googling outside of his notes was so much more better for understanding regression!
por Daniel M•
Un curso difícil de entender si no tienes la base matemática de regresión. Uno no sabe por dónde empezar, cualquiera de los cursos de esta serie (Statistical Inference, R programming...) pareciera que te saturan de información. Es bueno para curiosos con bases en R y que quieren saber más de Regresión
por Siddharth T S•
Both the video lectures and the book coast through some important topics that they should have spent more time explaining. The homework exercises and quizzes are definitely useful, but the subpar teaching efforts meant that I had to refer to outside sources for understanding the key concepts.
por Jing Z•
I just realized that you have to upgrade(pay $49) in order to submit the quiz and receive the feedback. That's depressing since my purpose is to watch the video and check out what I learned so far without getting any certificate. The policy here bring huge inconvenience for people like me.
por Grigory S•
One of the most difficult courses in the whole programme. From my point of view it is very important, but not so well explained. I had to go through other training sessions in order to understand the concept based on numerous practical examples and then return to Coursera to finish it up.
por Stefano G•
I love the content but:
imprecision (a lot),
lack of explanation
for one of the most difficult subject in the specialization.
Last commit/update for the video from the teacher 1/2 year ago: are the materials update?
por Coral P•
I would like to propose that instead of putting the optional reading materials at the back, it should be put up front and mandatory. Else we can't follow the videos
por Jorge P•
Should cover a lot of dfificuties when the model assumptions are violated and should be for a longer time or having a second course about this theme.
por João R•
Needs more practical examples. Could be rerecorded. I love mathematical theory but past week 2 it is really too theoretical, in my opinion.
way to much emphasis on non-data science. This one course covers more information that the rest of the courses combined..
Very difficult. Needs homework problems guided by videos like Statistical Inference coarse to make easier.
por Polly A•
Would love to "Unenroll" but can't.
Can someone please take this course off my dashboard?
por Albert B•
To fast pace and missing lot of content to make this lesson enjoyable!!!
por Rezoanoor/CS/Rezoanoor R•
The course was nowhere near of interesting. It was arduous and boring.
por Izabela E•
Difficult, fast peaced and not well explained. Requires a lot of work.
por Sepehr S•
The instructor is not good and doesn't explain things clearly.
por Daniel R•
Some topics that are important, are obviated
por Joseph D•
Coursera keeps changing my rating. Not cool.
por Ankit S•
not effective for new learnners
por Vicky G•
I seldom write critical comments for Coursera courses because the many courses I've taken have been quite well-designed so far. This one I feel obliged to write something, which may or may not make a difference judging by how much care was given to designing this course in the first place. From the resource allocation perspective, this course does more harm than good because the minimal amount of knowledge you gain from this course is not worth the amount of time you spent trying to figure out how the lecturer perceives and conveys statistical concepts in such a confusing way.
Bottomline: if you don't need the Data Science specialization certificate from JHU, you are WAY BETTER OFF by taking the Basic Statistics + Inferential Statistics courses provided by University of Amsterdam. I completed those two courses myself. The lecturers there truly made an effort to make the materials as engaging and intuitive as possible. You will not waste your time by taking those courses instead.
If you thought the Statistical Inference course was bad enough, try taking the Regression Models course. It refreshes your understanding about how bad a course can be. Below are some major problems:
1. The delivery of the materials is very dry. I can't tell if meaningful effort was put into creating engaging examples so that students can better understand the material. The mathematical and theoretical parts were poorly explained with inconsistent notations and insufficient elaborations about the concepts. The lecturer often jumps from very basic concepts to very advanced/complex concepts without enough transition/explanation. I had to constantly consult a friend who's very good at statistics to bridge the gaps.
2. The lecture notes are way too chaotic. Many times the PDFs provided do not match what was shown in the videos at all. Several pages in the PDFs were not covered by the video lectures, and vice versa.
3. Stepwise regression was not even covered in this course. Many students ended up using stepwise regression for the course project. Maybe students are just jumping ahead before applying the more fundamental techniques covered in this course, or maybe stepwise regression should have been covered??
4. I wish there were a lecture at the end that walks through one case study and applies most of the core techniques covered in this course. In Roger's Exploratory Data Analysis course he did one at the end and applied many things he taught in the fragmented lectures in an integrated manner. That was super helpful.
Some minor good things about this course that I did not gain from the UvA courses:
- The hodgepodge lecture provides some very interesting materials.
- The simulation examples about covariate adjustment are quite intuitive and facilitate understanding.
por Derek P•
The course is essentially just a review of formulas with very little intuition explained to the beginner. It was necessary to use a collection of outside material from other courses and readings to learn the concepts. This course needs to be completely redone with a focus on developing a student's intuition for the material and then support this intuition with basic examples that build as the course progresses. A fundamental demonstration of how to use R to work through regression models (starting from square one) should be added so that this becomes a self-contained course. As it currently stands it is a collection of poorly integrated slides and concepts that serve to confuse the student more than educate. Other classes teach this material infinitely better.