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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
2,288 classificações
483 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 :)

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51 — 75 de 484 Avaliações para o Understanding and Visualizing Data with Python

por FREYA J

11 de jun de 2019

I love the depth and breadth of the content. It provides in-depth knowledge of statistics and wide range of context information and supplementary reference learning materials. I also appreciate that each lesson is accompanied by hands-on activities using Jupyter notebook which definitely has helped me gain a deeper and clearer understanding of the content.

por Geetha A

5 de dez de 2019

The course gave a very good understanding to type of data (quantitative, categorical) , histogram, correlations, standard terms used in statistics, how sample plan needs to be created . The peer review exercise was very nice. I enjoyed doing it. The exercises in python looked basic. Overall a very good course and I enjoyed learning through this.

por Punam P

5 de abr de 2020

Very nice experience to join this course, which help me to understand and visualize the data using python. I recommend this course to everyone and too friends, as all the instructors clarify all the concepts so nicely. I Thanks to everyone involved in this course to gave me opportunity. Thanks to Coursera for giving such platform.

por snehil

24 de mar de 2020

This first course in the specialization was very helpful and outstanding in the way it created the concepts of statistical programming and data visualization along with statistics theory. All instructors were very helpful and my special thanks to Brady T. West and Brenda Gunderson who were splendid in their teaching methodology.

por Amelia M

7 de jun de 2020

I really love this course! This has been my best learning experience since I use Coursera! I really appreciate Brian to answer our questions in the forum, even though some of my question is really silly, but he is also very patient. The content of this course is very nice, I learn a lot. Thanks for the efforts of every staff!

por Wei O

31 de mar de 2021

Out of all the Python courses I can find, this course from U of Michigan is the most fun and interactive lesson I ever seen on Coursera! I would highly recommend University of Michigan to anyone. Easy to understand, yet challenging enough for critical thinking. Thank you Professor and Associates staff for your hard work!

por Mradul T

3 de jun de 2020

The course content is GOLD! Seriously, several of the things that were taught in this course are already known to me but after taking this course, it gives me the real insight and physical significance of those things. After this course I understand how to actually use those things practically! A must do course 🤩😮🤩🤩

por Elena G P

19 de mai de 2022

T​he course is very informative about summary statistics and distributions, Pandas, Matplotlib and Seaborn library. The forum is 5 stars, like the whole course.​

O​nly the last week could be improved by adding more quizzes and practice.

"​Univercity of Michigan", you are the best! Thank you very much for this course!

por Shekhar N

14 de abr de 2020

A very gentle introduction to data visualisation with great effort from teachers and students to make the course refreshing.

The course will not be very mathematical or coding heavy.

Most of the quizzes are fairly simple and motivate the student to gain more insight by opting for further courses in the specialization.

por Maksim M

11 de fev de 2020

This course gives a solid understanding of core statistical principles, sampling, approach to making inferences, plus some experience with data manipulation using Pandas and data visualization using Matplotlib and Seaborn libraries, as well as some experience with the Numpy library (all in Python)

por Sidclay J d S

31 de ago de 2020

The course is really good, videos and materials presented are good, there are lots of recommendations for additional readings and web tools, it is also interesting the change of presenter, it helps to keep attention. But I think it is not for somebody who has never heard of Statistics before.

por M N

28 de jun de 2020

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.

por Giuliano M

26 de mar de 2020

This course is excellent and very well thought out. It covers the fundamentals of sampling methods and data analysis as well as their practical applications with Python. I would recommend it to anyone willing to learn statistics (but you should already have some basic Python knowledge).

por Christine B

19 de jul de 2019

I feel 100% more confident in my job now. We just started using Python for analysis and I am probably now ahead of many of my coworkers in a super short amount of time. The class got me over the hump in the learning curve so I can progress much faster than trying to learn on my own.

por Soumyadeep S

5 de jul de 2021

Probably the best course on internet to learn Statistics, understand why you are learning it and also getting the mathematical essence. Visualizing the data solves half of understanding problems and this course has a lot of it. Thank you for creating such a wonderful course.

por HUNG H L

16 de jun de 2019

Sometimes, the lines in Jupyter notebooks are kinda hard to understand. Yet, there are a lot of materials out there online for us to explore; for this, I also learn how to solve programming problems by myself. In general, I like the courses and the instructors a lot.

por Colin F

14 de dez de 2020

Great refresher course for those who have taken courses in statistics previously, or a really good introduction for anyone new to the subject. Also a great introduction to using Python for statistical analysis. Everything is clearly laid out and easy to follow.

por James B

10 de mai de 2020

Great course. The materials are thoughtfully put together and paced well, and I achieved my learning objectives: a second pass through undergraduate level basic statistics and a basic idea of how to use python to do math an evaluate statistical and other data.

por Toby C

25 de nov de 2020

An excellent combination of lectures and labs. The material is extremely well taught. The mixture of lecturer styles helps to maintain interest. There is good additional content available for the deep dive topics. I found the content fresh and relevant.

por AQUINO, A M (

29 de out de 2020

This course is such a great course for beginners in Python like me. It has very helpful reading materials to aid you and great tutorials for Python using Jupyter Notebook. This made me excited to explore Python for statistical analysis in my research works.

por Sanjoy S

26 de abr de 2020

This course provided a valuable introduction to data handling and visualizing with python. I very much valued the mix of videos, readings, and Jupiter notebook work, as well as all the pointers to additional resources for deeper dives. And the cartwheels!

por Fryderyk Ł

13 de nov de 2021

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.

por Benjamin D

27 de mai de 2021

Excellent course. Well-paced, about right difficulty, and useful knowledge all around. Instructors were engaging and fun to listen to. The course managers seem to obviously care about this course, and the result is that the quality feels top-notch

por MMR

10 de jan de 2022

An excellent course that helps to grasp the ever elusive central limit theorem and its application to simple random sampling. It provides solid foundation for learning hypothesis testing and statistical inference. Coregulations team. Great work.

por Richard R

15 de abr de 2019

A well paced stats refresher which covered the core material well and skillfully introduced current research. The fourth week was a solid introduction to sampling methodologies and inference. Looking forward to the next course in the sequence.