Python is a core skill for anyone working with data—and this course shows you exactly how to use it in practice. Through real-world examples, you’ll build an end-to-end data analysis workflow using four of Python’s most powerful libraries: NumPy, Pandas, Matplotlib, and Seaborn. You’ll start by loading and cleaning messy datasets, then move into common statistical analysis and transformation techniques.
Data Analysis With Python
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
4 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Use NumPy/Pandas, load and clean data, analyze statistics, and visualize insights with Matplotlib/Seaborn in Jupyter for data science tasks.
Details to know
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Assessments
1 assignment
Taught in English
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There are 6 modules in this course
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