Great course to start with Statistics. Methods of data collection and their implications are explained in good detail. Good start with coding in Python visualizing data as well.
Understanding and Visualizing Data with Python
Understanding and Visualizing Data with Python
This course is part of Statistics with Python Specialization
Instructors: Brenda Gunderson
Access provided by Ministry of Public Administration of Slovenia
150,774 already enrolled
4.7
(2,711 reviews)
Beginner level
Recommended experience
Flexible schedule
1 hour to complete
Learn at your own pace
95%
Most learners liked this course
What you'll learn
Properly identify various data types and understand the different uses for each
Create data visualizations and numerical summaries with Python
Communicate statistical ideas clearly and concisely to a broad audience
Identify appropriate analytic techniques for probability and non-probability samples
Skills you'll gain
- Data Analysis
- Jupyter
- Data Visualization
- Statistical Methods
- Box Plots
- Matplotlib
- Descriptive Statistics
- Statistical Analysis
- Statistical Inference
- NumPy
- Exploratory Data Analysis
- Statistics
- Statistical Visualization
- Sampling (Statistics)
- Data Visualization Software
- Probability & Statistics
- Histogram
- Python Programming
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
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This course is part of the Statistics with Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
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Learner reviews
4.7
2,711 reviews
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Showing 3 of 2711
RK
4
Reviewed on May 14, 2022
AS
5
Reviewed on Mar 2, 2021
20 studying hours that helps me getting back to speed on manipulating the quantitative data in Pandas with different query conditions, powerful statistics and Sampling Distributions.
VV
5
Reviewed on Aug 2, 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 :)
