Skip to main content
grasp.study
About
Explore
Pricing
Log in
Try it for free
Back to course
👋
Welcome to a Grasp lesson
Create a free account
to keep studying and create your own study path.
Data Science Internship Prep
·
Module 3
Data Visualization and Exploratory Data Analysis (EDA)
1
Matplotlib Fundamentals: Creating and Customizing Basic Plots
Create fundamental plots (line, bar, scatter) with Matplotlib and customize them for presentation.
2
Advanced Statistical Visualizations with Seaborn
Build advanced statistical visualizations (histograms, boxplots, heatmaps) with Seaborn.
3
Exploring Relationships: Correlation Matrices and Pair Plots
Analyze relationships between variables using correlation matrices and pair plots.
4
Detecting Multicollinearity with VIF
Detect multicollinearity in features using the Variance Inflation Factor (VIF).
Time-Series Analysis: Resampling & Rolling Windows
Handle and visualize time-series data, including resampling and rolling window analysis.
6
Real-World EDA: From Data to Insights
Conduct a full EDA on a real-world dataset, documenting findings and insights.
Crafting Portfolio-Ready EDA Notebooks
Structure an EDA project as a polished Jupyter Notebook for a portfolio.
Publishing Your EDA Project on GitHub
Publish the complete EDA project with a professional README to GitHub.
Previous module
Data Science Foundations: NumPy and Pandas
Next module
Machine Learning: Core Concepts and Workflow