Worth Learning

great course

nice effort

Keep it up

In overall the course is good. However, there are some issues that could be improved, as for example:

- Using the NHANES database is come cases is not the most effective as you can spend some times trying to indetify or search for the variable they are asking for. Better instructions or the use of a simpler database could be an alternative.

- Some videos could be improved. There are compilation errors in the Python demostrative videos, in some other cases previoulsy not-explained functions are used (while similar functions already known by the alumn are available) or Python 2 functions are proposed (the course should be oriented to Python 3).

- I found that both parts of the course (stats and programming) are not always perfectly coordinated.

Despite these issues, the course is good and I will go to the next course with them.

Overall good but still have rooms to improve. I knew so little about statistics and Python. The concept is quite difficult but relatively new unlike other typical statistics courses offer. Practice assignments are very good but difficult. More guidance of Python libraries usage would help. Passing assignments were too easy. Strong foundations of using Python especially in libraries such as matplot, numpy, panda, seaborn would really help to better understand the concepts with a graphical presentation in Python. I would recommend this course for those who are familiar with those Python libraries already. For me, I need to learn more about those and would revisit the content here again to better grasp full understanding.

The topics that were seen in the course started in a very basic and understandable way but they evolved to much more advanced and difficult topics without a good explanation.Sometimes I felt no connection between theory and practice with Python. The large number of teachers does not allow continuity in learning and creates gaps.

This course started well, but unfortunately, I think they should add more extra example and focus on the topics more in-depth, I can say in each quiz I spend around 3 hours to find related topics in the internet and learn them to answer to the questions and I think it should be cover by the course itself.

It's great course to understand the basic concepts of statistics like uni-variate and bi-variate data.But,the assignment which they give week 3 and week 4 is not that much to implement the concepts practically. Overall ,it is a good course.

Good stats course. Needs more Python. Much of the Python is just watching or clicking run. Would appreciated more opportunity to walk through the coding with hints and hidden solutions to gain some proficiency.

There is incorrect course title for this course as in reality it’s Statistics AND partial illustration of it using Python. There is no consіstent exposition on Python libraries and frameworks.

I think the order of lab components should be rearranged. Introduction of core python mechanics should come before the module in which each code is implemented.

Very long videos, even the simplest concept is explained in a slower manner. But this is true for me and a lot might benefit from this pace.

Lectures are boring and very long it should be more practical ,but yes I've gain certain statistical insights.

Python in week 2 is largely unexplained, also course could have dived deeper into statistics

Good content and syllabus, though the later videos could be easier to follow.

I think it was more theoretical and more practice is required.

Well taught, it will be hard for beginners with python.

Too many texts in the lectures

A little easy, and lacks focus

Could be more refined.

phyton part is shit

Basic statistics explanations are good, especially for those uninitiated. Examples that require intuitive understanding of plots are nice, albeit slightly confusing.

A lot of material concerning Python is not covered in the course, however. No possibility to download source files and work with them in your own environment. Ambiguous instructions that relate to statistical concepts that are still unknown and lots of materials that require 3rd party explanations. This extends the learning time 4-5 fold.

Extremely long weeks with lots of technical and incomplete materials. Breaking things into smaller chunks would have made a world of difference.

Very poor.

Had a hard time keeping my attention. Very lecture heavy. In fact, astoundingly lecture heavy. This course should have gone between the jupyter notebooks and the video content to keep the viewer engaged. Why not leverage python and jupyter to teach concepts as the student follows along instead of just lecturing for hours? Keep the students engaged through hands-on work instead of just talking at them for hours. The structure is simply antiquated for the modern student.

The statistics material is extremely superficial and naive to anyone with high school level of statistics. On the other hand, the Python lessons are extremely difficult, going directly to complex tasks with no explanation of the intermediate skills required to understand what is being taught. This is the case even if the course description says only a basic level of Python knowledge would suffice to follow the course. I don't see how this course could be useful to anyone.