Applied Plotting, Charting & Data Representation in Python

Besides, the design of practice is not very good as well as first class 'Introduction to Data Science in Python'.

In my work I have plenty of opportunity to apply data science and very little knowledge on how to.

If you do love data science, and apply what you learn on the course, with some grit and perseverance, you'll prevail.

The previous course in this specialization (intro to data science in python) by comparison has many more guided practice exercises, and I am disappointed that this course does not live up to the standard set by the first course.

The lecturer is amazing and I learned tons of information about publication quality charts and data cleaning.It takes plenty of time though.I recommend this course to anyone serious in learning data science.

I think a must to go further in Data Science A fundamental issue after this course is that it still takes me hours to prepare an appealing data visualization using what I learned here whereas with Excel it takes me minutes to draw and pretty a graph.

This course will teach you a lot if you want to work in the data science / ML field ... and require a lot of your time.

very essential for data science Loved the course!

Great course to learn charting in python - recommended for data science The course is good.

Interactive IPython notebooks enables creativity to implement lecture notes right in the browser during watching lections.I enrolled to "Applied Plotting, Charting & Data Representation in Python" course right after finishing the first "Python for Data Science" module.

This knowledge is very useful and applicable in many situations when doing data science.

I am hoping there will be a second part to this course, focusing on real-world data visualization problems and converting graphics, with newly acquired data science skills from other courses in the series, into a full portfolio.

I'm okay with the peer review system.

Also, I enjoy the peer review assignment.

If you enjoy reading academic papers and peer reviews then this course is for you.

I was skeptical about the peer review format at first, but then I embraced it - good choice!

Another problem with this course is the peer review, the grading policy should be changed to punish irresponsible reviewers, no useful feedback got.

Well formulated lectures, and interesting and challenging assignments - at least you can make them as challenging as you like..Initially sceptical about the peer review system for this kind of learning, but actually received good and clear feedback, and was able to see the learning and approaches of other people.

Peer review of assignment is very time sensitive.

The Peer review system is good, but the evaluation method should be more elaborate Good course mostly focused on personal work and assignments.

I am not too crazy over the peer review assignments plus the course was hard to follow Very good course.

Such a good course!Dr Brooks is an amazing teacher.Assignments are hard as always but you are forced to learn alot.Peer review was fun except last one where I only review people that didnt put in any effort:(Thanks Dr!

The course can be summarized as: "OK, here are some tools that can be used: now read the documentation, Stack Overflow and some papers that we give you links to".

The professor basically tells you what can be done using matplotlib, give you a cursory example and leaves you all on your own to understand what actually happened by referring to sources such as google or stack overflow.

Assignments are not very easy/simple, but completing it with real data and help from documentation, stack overflow and discussion forums is deeply satisfying.

I'm a fan of learning by doing, but I question the value of a course when most of what I pick up I get from stack overflow.

But for me also required a lot of self-learning from Stack Overflow in order to make attractive charts.

I now know enough to go to stack overflow and matplotlib documentation and figure out what I need to get done, so my goal is accomplished, but my understanding of the plumbing of the different commands feels a big hazy.

Though, since this course is about plotting and charting there is a lack of visual materials and great examples of use cases.

Helped in developing thought process hm... its very helpful but too compact which i need to find in internet myself to understand I was a bit apprehensive about this part, but once the course progressed the options for plotting and charting became clear, I learned a lot about this subject and I could have done with this information years ago !!

In addition to giving practical guidance in plotting and charting, the professors also give a simple but comprehensive explanation of the structure and functioning of the matplotlib.pyplot module, even though it doesn't require you to understand the deeper structure when you use the function, it certainly doesn't hurt you for learning more, especially when you want to be an expert in this.

Additionally, neither you nor your peers are qualified to grade the assignments, because you’re just learning how to curate and present data (if you’re not already a scientist and just want to learn how to do this in Python).DISCUSSION FORUMS: You won’t find answers or discussions in the discussion forum.

Discussion forum is quite supportive.

Very good assignments and discussion forum.

Pretty well structured class, but quite expensive considering very limited lectures and assignments that are mostly "find your own challenge on the internet".

Great Course to learn Data Science Well structured The course itself is great.

Excellent course... great The course content is of good quality and well structured to help student learn the concepts easily.

Well structured course, gave a nice overview of the matplotlib tool and the basics for data visualization.

However, as a fundamental course of introduce plot in python, I don't think the course is well structured.

Nice Course for learning python It's a good intermediate level course .

Learn alot, but intermediate level, so you have to learn alot on your own and fill any gaps you have.Great jump start and overview into real visualization.

It is an intermediate level course.

Seemed more introductory, here are the tools - go have fun rather than actually teaching teaching 这个课程作得相当棒， 绝对值得推荐。 I continue to like the way the Prof. Brooks explains the different topics, the selection of the topics themselves and the scientific articles are very enriching.

I think there there is too much time given to the esoteric of what makes plots pretty rather than the nuts and bolts of how to do it and the limitations of using Pandas and Matplotlib for real world data I found the lectures interesting and thorough yet short and to the point.

If you've had some experience with python and got your explanations for plotting from somewhere else, you'll mostly spend more time looking for data to present than for the actual assignment.I don't understand why there's no selection of graphs and data sets to choose from so you can concentrate on programming and properly presenting data rather than wasting your time looking at reddit like recommended by the instructor.ASSIGNMENT GRADING: You’ll have to grade your peers’ assignments with a rubric that’s just not working: you can give points for someone uploading an image/writing a paragraph of text, but you have to either give 0 or 100%, so there’s not way to properly grade partially wrong answers.

The final assignment give opportunity to do a little independent data gathering / wrangling / visualisation mini-project.

Good course, I liked the final assignment which gives the opportunity to freely explore data.

But the final assignment is not as said before as a deeper dive into source code of the lib.

Like that its peer reviewed.

I highly recommend this course to everyone Good course, I particularly enjoyed the peer reviewed assignments, it was fun to learn the different methods that people employed.