PSDV Teaching Resources
Interactive Jupyter Notebooks for Probability, Statistics & Data Visualization
Keywords
probability, statistics, data visualization, jupyter notebooks, python, education, machine learning, data science, interactive learning
Welcome
This comprehensive collection of interactive Jupyter notebooks provides educational materials for Probability, Statistics, and Data Visualization. Developed by Prof. Nipun Batra at Indian Institute of Technology, Gandhinagar.
Course Overview
ES 114: Probability, Statistics and Data Visualization is an undergraduate course covering:
- Probability Theory: From basic concepts to advanced distributions
- Statistical Analysis: Expectation, variance, and key theorems
- Data Visualization: Creating meaningful insights from data
- Practical Applications: Real-world datasets and machine learning
Key Features
- 24 Interactive Notebooks
- Complete coverage from probability basics to machine learning applications
- Rich Visualizations
- High-quality plots, interactive widgets, and mathematical demonstrations
- Self-Contained Learning
- Each notebook includes theory, code examples, and practical exercises
- Real Applications
- Work with datasets including MNIST, height-weight data, and word embeddings
Quick Start
Browse Online: All notebooks are available in the sidebar navigation
Run Locally:
Course Information
- Institution: IIT Gandhinagar
- Level: Undergraduate (No prerequisites)
- Current Course: ES 114 - Spring 2025
- Repository: GitHub
Reuse
MIT
Copyright
Copyright 2024-2025, Prof. Nipun Batra, IIT Gandhinagar
Citation
BibTeX citation:
@online{batra,
author = {Batra, Nipun},
title = {PSDV {Teaching} {Resources:} {Interactive} {Notebooks} for
{Probability,} {Statistics,} and {Data} {Visualization}},
url = {https://nipunbatra.github.io/psdv-teaching/},
langid = {en}
}
For attribution, please cite this work as:
Batra, Nipun. n.d. “PSDV Teaching Resources: Interactive Notebooks
for Probability, Statistics, and Data Visualization.” https://nipunbatra.github.io/psdv-teaching/.