Python for Data Science
Completed by Cristian Ramirez Calderon
March 23, 2026
39 hours (approximately)
Cristian Ramirez Calderon's account is verified. Coursera certifies their successful completion of Python for Data Science
What you will learn
Build pandas pipelines to clean, transform, and aggregate real‑world datasets.
Perform EDA and compute descriptive statistics to summarize data quality and behavior.
Apply hypothesis tests (t‑test/chi‑square) and interpret results for business decisions.
Create publication‑quality charts (bar/line/box/heatmaps) with matplotlib & seaborn.
Skills you will gain
- Category: Data Science
- Category: Data Transformation
- Category: Descriptive Statistics
- Category: Statistical Analysis
- Category: Feature Engineering
- Category: Data Preprocessing
- Category: Data Manipulation
- Category: Exploratory Data Analysis
- Category: Seaborn
- Category: Pandas (Python Package)
- Category: Correlation Analysis
- Category: Plot (Graphics)
