Retour à Understanding and Visualizing Data with Python

4.7

306 notes

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62 avis

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....

Apr 04, 2019

Excellent introductory course to statistics. Great use of NHANES dataset to demonstrate techniques on real dataset. I would appreciate a more demanding project at the course end.

Jan 24, 2019

I strongly recommend this course to those who want to begin python programming applied to statistics. It launches a very sound foundation for statistical inference theory.

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par Daniel R

•Feb 22, 2019

Lectures are great but there's little practice material and the quizzes are terrible. The quizzes are actually super easy but they don't cover much material from the course and sometimes introduce concepts and terms that were nowhere in the course materials.

If you want a good intro to stats without any actual testing, the lectures get pretty in-depth and the explanations are excellent! But if you're looking for lots of practice with stats in Python, you won't get much here.

par David W

•Apr 14, 2019

I love the U of M courses! I get so much out of them. Thank you again for helping me to advance my knowledge of Python and deepen my understanding of statistics.

par Kristoffer H

•Jan 10, 2019

This course still has spelling mistakes in its quizzes, which in a programming focused course are big, and the instructors don't seem interested in fixing them. The result is you have to guess through their mistakes if code is suppose to not work in a quiz because of the error or the error is not supposed to be there in the first place and the code is valid.

par Md I

•Apr 19, 2019

This is the best course in this website in entry level

par Aayush G

•Apr 15, 2019

I must say that this is a must take course for ones who are aspiring a career in Data Science. All the concepts were laid out so beautifully and it was explained very clearly with visualisations of each real-life-examples. I enrolled in this specialisation before starting my Machine Learning so that I have all the necessary fundamentals of Statistics. Brady Sir & Brendra Ma'am are simply phenomenal, the way they explain the concepts are incredible. The concepts gets etched in one's memory. The most exciting part of the course is Brenda Ma'am performing a cartwheel !! For all the ones who are enrolled, don't forget to watch it out.

par Jan T

•Aug 07, 2019

More hands on assignments would be desirable.

par José A G P

•Apr 16, 2019

The course contents are good to an introduction or refreshing in statistics but the assigments are not really well prepared, and contains many unrepaired errors. This drops down the level an educational potential of this course (and the entire specialization) and converts it in a poor educational resource and a waste of time, in my opinion

par EDILSON S S O J

•Jan 01, 2019

Amazing course!

par Yaron K

•Jan 26, 2019

A good introduction to visualizing data using the Python seaborn library

par Jin S

•Feb 06, 2019

Really enjoyed the different (yet all wonderful) teaching styles of the large instructor team!

par Frank S Y R

•Jan 17, 2019

Nice!

par Marko P

•Jan 09, 2019

Very good course which covers both statistical concepts and python application.

par Jadson P A d S

•Jan 24, 2019

I strongly recommend this course to those who want to begin python programming applied to statistics. It launches a very sound foundation for statistical inference theory.

par Moid H

•Feb 09, 2019

A good introduction on Statistics.

par Jorge A

•Feb 10, 2019

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par Rajesh R

•Feb 21, 2019

Very good course instructors ! Excellent balance of basics of statistics and python programming oriented towards data analysis. Thoroughly enjoyed the course material.

par Alejandro P

•Mar 07, 2019

Great approach.

par Fasasi t

•Mar 10, 2019

I love this course, the simplicity and explanation is excellent

par Patricia C G

•Mar 19, 2019

I loved this course! Thank you for sharing all your knowledge with us!

par Varga I K

•Mar 20, 2019

It was great setup for statistical analysis in python.

par cameron g

•Mar 21, 2019

Great introduction

par Rashbir S

•Apr 16, 2019

This is a must. If you want to be a data scientist then this course is like a stepping stone. Trust me its totally worth it

par Saleem R

•Apr 03, 2019

Excellent course for beginners from any subject related to engineering or science and who want to do research.

par Nirmal M

•Apr 19, 2019

I strongly recommend this course to those who want to begin python programming applied to statistics. It launches a very sound foundation for statistical inference theory

par Richard R

•Apr 15, 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.

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