Ratings and Reviews for Understanding and Visualizing Data with Python

So far the best statistics course I have taken on Coursera! High quality lectures and wonderful lecturers. The only thing I didn't like is the order arrangement of the homework. It started too hard, but once you overcome that, the rest is pretty doable.

This "Understanding and Visualising Data with Python" training offers: 1. lecture videos teaching you concepts 2. graded quizzes 3. a graded assignment where you have to create a survey design 4. Jupyter notebooks with exercises for you to explore statistical concepts in Python 5. walkthrough videos on Jupyter notebook exercises if you need some help to unblock yourself or when you want to understand why certain things were done The training was alittle lengthy but well worth the time. At times, because concepts can be explained in long sentences, you may need to rewind and revisit certain parts of the videos to get the full meaning of what has been explained. Overall, this training refreshed my understanding of: 1. basic statistical concepts - statistical measures, population, sampling 2. using numpy, matplotlib, seaborn, scipy packages in Jupyter notebooks (which was good because I currently dont code in Python at work) This training also explained practical ideas such as: 1. stratifying, clustering, why these concepts are important when sampling 2. issues with certain sampling approaches 3. useful ways to turn a non-probability sample into a probability sample, so that the analysis/claims you present would be grounded in a more solid basis. Points 2 and 3 in the list above were neither covered in school nor statistics texts in the past. So like me, you may get the chance to learn something new to apply to your work.

Completely Worth It

This is a good courses, it helps a lot of things, thank !

Great course and anyone can do it without any prior knowledge of statistics and Python

I've learned a lot from this interesting introductory course. I greatly appreciate all the hard work that the course design group members have put in, and I would like to recommend the course to my peers and friends. :)

Very good introduction to the concepts and corresponding techniques to implement/visualize these sophisticated and somewhat obscure theories providing a systematic view on the fundamentals. Great job! However, wish Prof Brady could go further in the detail on the non probability modeling and how to handle missing data. Maybe in the later courses in this specialization?

Very good level of teaching, nice and clear instructions, good introduction to the topics of statistics, sampling and drawing all sorts of graphs, histograms and such. I reccomend it to anyone, no previous Python or statistical knowledge is required.

Very excellent course . Right now I know how to apply descriptive statistics in python in professional way. Thanks coursera and University if Michigan for this opportunity.

Well, those sampling courses couldn't be more beneficial. It answered many questions i my mind. Thanks Umich and Coursera for the solid course!