Really helpful. the course material is excellent and the assignments are just right for testing the material. although you could use a bit of a more straight forward communications in terms of how to bets tackle assignments.

Data science is itself a very broad topic, In this course, they have tried to get in touch with all basics of data science, TO BE HONEST, you will not get everything thought in this, you have to put your own hard work in it.

Tougher than expected. Definitely requires one to have advanced programming skills. Assignments are a level higher than what is taught in the video. Not recommended for beginners but overall one of the better MOOCs out there

There is less focus on syntaxes which slows down the learning process as most people are still struggling with that. Other than that the course material and the instructor are very helpful. The grading system has some flaws.

Completed the course and found it pretty good for the first run. Mostly focused on the Pandas library - you'll be ok if you know a bit of Python, or have experience in another language.

Looking forward to subsequent courses.

The course it's very good and I'm not giving 5 stars only because I think it is very fast paced. This could complicate the process of joining the pieces together and it's kind of a big leap from the videos to the exercises.

This is a good course for practical hands on data in python. Good learning on map, apply, groupby, merge, data slicing, subsetting data, datetime, bin. creation

Should include datatime & cut in the assignments.

Thanks,

Suman

Great application of Python (really more about Pandas than Python) to data science applications. Course materials and instructors were helpful, though I do wish that the assignments were a bit clearer in their instructions.

An extremely demanding course, especially on the coding exercises. Expect long stretch of time on Stack Overflow to look up codes and examples....

I almost give up on this one, but still managed to get through after 5 days!

Excellent introductory course to Pandas. Four stars because the pace of the videos are too fast and the assignments requires, sometimes, excesive individual learning. Hopefully the info found in the forums is very helpfull.

Overall a very good course. Unfortunately, the instructions to some of the assignments are often confusing or simply wrong. Be sure to check out the discussion forums for clarification about what you are being asked to do.

You may need to brush up on some Stats concepts if you havent used them before. The assignments are sufficiently challenging, even if you have a programming background. Overall a good course to get started on Data Science.

Theory covered is minimal compared to the level of assisgnments, but i feel assignments are the best part of the course. To complete the asignments you need to explore a lot on your own and learn a lot too in the process.

Very good course to start with data science with python. Only thing you need is statistics background knowledge to better understand week-4 contents. But author has provided with reference to a free pdf book for the same.

The course is useful and I learned interesting techniques. It was just a bit too short in my opinion. I also think there could be more examples to show the best practices of using Numpy, SciPy, and Python in data science.

This course provides a brief overview of what data science has to offer. Professor Brooks has a great command of the concept of data science. I found the course assistant a little difficult to follow with and comprehend.

The interactive python notebooks and the programming assignments are excellent. The course loses a star for the incredibly fast pacing of the lectures, and the off topic data science assignments.

Still highly recommended.

The content is excellent (useful material and instructive assignments). I would have given it a 5 if I hadn't wasted a lot of time on mistakes/ambiguities in the assignment instructions, autograder rounding errors, etc.

pretty tough even though i've been playing with Pandas in the past. But learnt many new techniques. assignments are challenging. It takes more time than what is written. I spent between 16 to 24h on each assignement...!

The staffs are very good at making difficult key points clear and this is a very good course for data science starters. But the auto grader is not good, sometimes I have to debug not for my code but for the auto grader.

Good base material on data science. Not the best python course. Directions were lax during the programming and I stumbled around until I found the formulas they were looking for. Not the best direction on assignments.

Assignments are too difficult，cause if you don't use some special functions like extract（），you will have to stack lots of iterations···but some skills and functions used in assignments are not mentioned in the lecture.

No me pareció que fuera un curso introductorio, por el nivel de las tareas y por la explicación básica que daban de cada tema. Sin embargo, el curso me ayudó a desarrollar habilidad en manipulación de datos con Pandas.

Everything was pretty good and the assignments were challenging enough to help increase the skills of the students opting for this course, but a bit more video lectures could be added to the fourth week of the course.

The course content and explanation is superb, Assignments shall have access to course auditing students also though they shall not be graded, anyways thanks to Prof. Christopher Brooks to deliver such great lectures.