Introduction To Data Science (Udemy.com)

This course is certainly not for beginners. So it cannot be an introduction to data science. You need to have strong foundation in R and statistics in order to be able to follow the course. I will get back to it, once I improve the other skills so I'll be able to take the most out of it.

I got some good overview over the field topics, but would have preferred more details on the actual tools. In turn, despite of explicitly not intending to give an introduction to R, entire chapters (most of section 3) merely addressed R basics (data import, data reshaping, ...). Net, I would've liked to have more focus on the actual methods both from a theoretical but also an applied POV (what is the actual interpretation of results from some of the sophisticated methods) and less so on R details.

This is not an Introductory course. It covers a lot of material some of it on advanced topics. Sometimes the authors explain concepts clearly, but other times they go off into what I call PHD speak where they gloss over terms or assume the reader knows what they are talking about. I will have to do some serious research to understand some of the concepts covered in this course.

As someone plunging into this without reading the recommended R Language info, it can be a bit overwhelming. But, this is the way I like to learn. I will probably go through this course a few times before I truly get it all, but I am really happy with how dense and informative the material is. Instructors are clear and terrific.

In my opinion, you should include hands-on along with your lecture. You are just explaining the scripts, rather go bit slow and ask the students to do hands-on. I was struggling to find test data. If i have test data i could have done step by step to understand in-depth.

I've written some code in R before and I was hoping that this course was not so basic in the field. I have to say that this course is a good brief introduction to machine learning algorithms and some other interesting topics, all of them business focused.

I’m an advertising writer by trade, not a statistician / mathematician. I’m passionate about bringing data science into the creative arena in a very practical, everyday way. That’s what I love about this course. That’s what I love about the book “Practical Data Science with R” by Nina Zumel and John Mount – the same people who created this awesome course. Their ability to cut to the chase, to give you the right amount of context and statistical knowledge you need to actually begin working with data is unmatched IMO. I have to confess, I’m a big fan of their book and tweeted about it. So they invited me to try a preview of this course. I don’t know them, nor have I ever met them. I fully believe this course takes the same intelligent, learn-it-in-your-bones approach to data that their book does. So if you’re interested in long-winded discussions with a lot of lengthy math expressions, this may not be for you. If you’re interested in doing actual hands-on, mining data for insights, this course (and their book) are at the top of my list.

Honestly I didn't expect that I had to write a review for a course when I just finished the 5th lecture out of the 28 lectures. The lectures so far have been good and clear, but I think it would be more appropriate and fair of the course organizers or udemy to request for rating at the end of the course rather than in the middle or even at the beginning of the course. Course wise the contents are clear and easy to understand so far. So long as you meet the recommended requirement (e.g. have some understanding in statistics/data analysis/R programming) the learning curve shouldn't be too steep for the students. As someone pointed in Discussion, the resolution is quite bad in full screen mode. This can be a bit troublesome for those with bad eyesight like myself when the lecturers are referring to the R coding console, but this could simply be udemy's side's technical glitch and shouldn't be the reason why students would stay away from the course.

Found a new way to create test and training sets! Looking forward to the individual models. I'm doing Logistic Regression at work and looking forward to learning new things. Might want to strive for consistency between the "

Great course, engaging and clear! The instructors complement each explanation with a practical application, which helps me better understand the concepts. I also love that they're providing all the data, code and scripts ! Highly recommended.

Nice course

looks ok so far