Python for Data Science
Completed by DAVID FERNANDO MONROY GUTIERREZ
March 31, 2026
39 hours (approximately)
DAVID FERNANDO MONROY GUTIERREZ'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: Feature Engineering
- Category: Data Preprocessing
- Category: Data Transformation
- Category: Data Processing
- Category: Data Wrangling
- Category: Statistical Hypothesis Testing
- Category: Probability & Statistics
- Category: Exploratory Data Analysis
- Category: Seaborn
- Category: Matplotlib
- Category: Data Cleansing
- Category: Plot (Graphics)
