Python or R for Data Analysis: Which Should You Learn?
February 4, 2025
Article
This course is part of DeepLearning.AI Data Analytics Professional Certificate
Instructor: Sean Barnes
Recommended experience
Beginner level
A basic understanding of Python programming would be helpful but is not required.
Recommended experience
Beginner level
A basic understanding of Python programming would be helpful but is not required.
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This comprehensive course guides students through the complete data analytics workflow using Python, combining programming fundamentals with advanced statistical analysis. The curriculum is structured across five interconnected modules that build upon each other, using real-world datasets to provide practical, hands-on experience.
Starting with programming fundamentals, students learn essential Python concepts while working with real datasets like public library revenue and restaurant safety inspections. The course introduces the Jupyter Notebook environment and transitions students from spreadsheet-based analysis to powerful programmatic approaches. Students master core programming concepts including variables, functions, and control flow structures. This course bridges the gap between theoretical knowledge and practical application, enabling students to become proficient in using Python for comprehensive data analysis, from basic data manipulation to advanced statistical modeling and forecasting.
20 videos9 readings4 assignments1 programming assignment2 ungraded labs
19 videos8 readings4 assignments1 programming assignment3 ungraded labs
13 videos2 readings3 assignments1 programming assignment2 ungraded labs
20 videos4 readings4 assignments1 programming assignment3 ungraded labs
10 videos2 readings2 assignments1 programming assignment2 ungraded labs
1 programming assignment
4 readings4 ungraded labs
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