Python for Data Science
Completed by Janit Jindal
November 6, 2024
39 hours (approximately)
Janit Jindal'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: Pandas (Python Package)
- Category: Exploratory Data Analysis
- Category: Seaborn
- Category: Statistical Hypothesis Testing
- Category: Data Transformation
- Category: Statistical Analysis
- Category: Data Processing
- Category: Data Analysis
- Category: Data Wrangling
- Category: Data Manipulation
