Chevron Left
Voltar para Understanding and Visualizing Data with Python

Comentários e feedback de alunos de Understanding and Visualizing Data with Python da instituição Universidade de Michigan

4.7
estrelas
2,270 classificações
480 avaliações

Sobre o curso

In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling. At the end of each week, learners will apply the statistical concepts they’ve learned using Python within the course environment. During these lab-based sessions, learners will discover the different uses of Python as a tool, including the Numpy, Pandas, Statsmodels, Matplotlib, and Seaborn libraries. Tutorial videos are provided to walk learners through the creation of visualizations and data management, all within Python. This course utilizes the Jupyter Notebook environment within Coursera....

Melhores avaliações

AT

21 de mai de 2020

Excellent course materials, especially the videos, with content that is thoughtfully composed and carefully edited. Very good python training, great instructors, and overall great learning experience.

VV

2 de ago de 2020

Great course to learn the basics! The supplementary material in Jupyter notebooks is extremely valuable. Really appreciate the PhD students who took the time to explain even the simplest of codes :)

Filtrar por:

451 — 475 de 482 Avaliações para o Understanding and Visualizing Data with Python

por k k

24 de fev de 2020

excellent course

por aditi a

26 de abr de 2020

Worth Learning

por Liu M

13 de jan de 2020

great course

por Ata M

1 de fev de 2019

nice effort

por Elvan V

30 de set de 2020

Keep it up

por 黄存昕

2 de jun de 2021

not bad

por Mikel A

14 de mai de 2020

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.

por maytat l

8 de jul de 2020

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.

por Anastasios B

30 de set de 2021

The title of the course is a bit misleading. The focus is really on some basic Statistics, with Python notebooks thrown in to demonstrate some of those concepts. However, you won't get much help understanding Python. Even the workbooks involved use some interesting methods/libraries, but not much detail in the course about them, other than the particular use they come up in. It's a 4 week course, but can easily be completed in about a week, possibly less. If you already have a fair foundation in Stats, this course probably won't add much value. I did enjoy the instructors and they were trying to keep things interesting.

por Mitchell H

25 de mai de 2021

Generally very good content and presentation. Removing a star due to frustrations with a really off topic essay assignment required in week 3 of the course. An online programming/statistics course is not the place to teach writing skills. This is especially true since the online peer review grading system isn't configured to ensure submitted essays are reviewed.

por Sig I

24 de mar de 2022

The course material seemed a bit scattered, possibly because of there being at least five presenters. The material wasn't really that focused on data visualization and veered into esoteric (but interesting) topics like non-probability sampling. The pizza memorandum assignment seemed quite pointless. More work with Python labs would have been my preferrence.

por Jaime C

8 de abr de 2020

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.

por Hossein P

1 de nov de 2019

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.

por kamalakannan

26 de jul de 2020

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.

por Khang V P

20 de set de 2021

The theory material is great. However, the final week has a bit exhausting content but the lab is way too easy. Additionally, there is no real "key answers" for the lab so I cannot double check my work.

por Vikram J

20 de out de 2020

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.

por Rakesh D

20 de jan de 2020

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

por Vignesh R

11 de nov de 2019

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

por Zhehao G

23 de mai de 2021

too much works in each week, It may be possible for people, who work only half day

por Leonardo S

11 de abr de 2020

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

por Ayush Z

19 de mai de 2020

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

por Navavat P

6 de set de 2020

Too many texts in the lectures

por Djon P

4 de abr de 2020

A little easy, and lacks focus

por Chunsi

22 de jun de 2020

Could be more refined.

por Yu J K

3 de dez de 2019

phyton part is shit