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Ratings and Reviews for Understanding and Visualizing Data with Python

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Reviews and Ratings

4.7

2,144 Ratings from Coursera

Reviews

awssem
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.
Excellent course to better grasp fundamental parts of statistics within the data analysis space and how to create some basic visualizations. The course is not Python heavy, although some experience working with Pandas, Numpy and understanding of basic loops and list comprehensions will help.
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.
Well taught, it will be hard for beginners with python.
It is a fairly good course for statistics introduction. However, the explanation on how to apply with python libraries is not well-organized. Learners must have a well understanding of numpy, pandas, Matplotlib and Seaborn on their own in advance, because the TAs just read through the code without explaining why in details. The statistics concepts lecturer is very good, but the TA didn't describe python libraries or modules selection and application concept.
From my point of view, this course was very fundamental for learning statistics with python . I have learnt a lot about different statistical model with how to describe by visualizing them. I have also studied uni-variate , multi-variate data analysis and introduced to a practical NHANES model which was implemented on python code to get different visualization of data analysis. Finally also learnt about using sampling distribution , sampling variance and probability and non-probability sample. This course will definitely boost up confidence for statistical analysis with python.
It is a very explanatory course with instructors trained in the subject. The class materials are varied, which allows new technical skills to be developed.
Amazing
Could be more refined.

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