Understanding and Visualizing Data with Python
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| Rating | 4.4★ based on 103 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 4-6 hours/week |
| Starts | Jun 19 (45 weeks ago) |
| Cost | $49 |
| From | University of Michigan via Coursera |
| Instructors | Brenda Gunderson, Brady T. West, Kerby Shedden |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Mathematics |
| Tags | Data Science Data Analysis Probability And Statistics |
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What people are saying
very good course
Very good course instructors !
Very good course which covers both statistical concepts and python application.
Overall a very good course and I enjoyed learning through this.
Beginner level of plotting and sampling phyton part is shit More statistics than Python but very good course Excellent course.
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very clear
All the concepts were laid out so beautifully and it was explained very clearly with visualisations of each real-life-examples.
Instructors and presentations are excellent, very clear.
It was an excellent course, the explanations were very clear and the examples given really helped to ilustrate the concepts.
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real life
there are none real life examples or detailed visualizations, except a few simple plots.
Definitely recommend it to anyone, who would like to refresh statistical knowledge, learn how to apply it in real life.
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data analysis
Excellent balance of basics of statistics and python programming oriented towards data analysis.
The content is very comprehensive, provides an introduction about all the useful things necessary to do statistical data analysis with Python.
for beginners
Excellent course for beginners from any subject related to engineering or science and who want to do research.
Great class for beginners.
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basic statistical
Good introduction to basic statistical methods with an emphasis on working with surveys, and a good introduction to basic statistical techniques with core Python, numpy, matplotlib, seaborn and statsmodels.
Great course to review basic statistical concepts.
experience with
Python exercises can be more interactive and the examples for sampling could be explained by taking a small data set for getting a realistic idea 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) Excelent This course is really a general overview.
That is an amazing course for someone, who has at least a little bit of experience with Python under the belt!
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| Rating | 4.4★ based on 103 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 4-6 hours/week |
| Starts | Jun 19 (45 weeks ago) |
| Cost | $49 |
| From | University of Michigan via Coursera |
| Instructors | Brenda Gunderson, Brady T. West, Kerby Shedden |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Mathematics |
| Tags | Data Science Data Analysis Probability And Statistics |
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