Scientific Computing From Scratch

A summer bootcamp on scientific computing for beginners with Python and Pytorch, organized by Pratyush Tiwary, University of Maryland.

All workshops will be held on Zoom from 4–6 PM Eastern time. Students only need a laptop — not an iPad or tablet — and a stable internet connection.

Zoom link has been sent to registered students. Videos will be uploaded below a few hours after each class.

Topic Dates
Python basics June 22–23, 2026
AI/PyTorch basics June 29–30, 2026
AI/PyTorch not-so-basics July 27–28, 2026
Vibe coding / Codex August 11, 2026

2026 Instructors include:
Jindal Shah, Oklahama State University
Venkata Adury, University of Maryland
Eric Beyerle, University of Copenhagen
Niranjan Sarpangala, University of Pennsylvania

Syllabus

Module Scope Notes Time
(Click to add to calendar)
Video
Introduction to python Basic syntax

Functions

Useful packages

Data handling

Colab June 22 4-6PM EDT 🎬
Visualizing data and Matplotlib Matplotlib

Basic plotting

Plot customization

Subplots

Colab June 23 4-6PM EDT 🎬
Matplotlib Basics of Matplotlib

Line plots

Visualizing errors

Multiple subplots

Contour plots
Colab Upcoming 4-6PM EDT 🎬
Pandas and sklearn Working with datasets Colab Upcoming 4-6PM EDT 🎬
Introduction to machine learning with PyTorch Part 1 Colab Upcoming 4-6PM EDT 🎬
Introduction to machine learning with PyTorch Part 2 Colab Upcoming 4-6PM EDT 🎬
More on machine learning with PyTorch Introductions to graph neural networks

PyTorch Geometric
Colab Upcoming 4-6PM EDT 🎬
More on machine learning with PyTorch Language model pre-training (NLP)

train baby GPT from scratch
Colab Upcoming 4-6PM EDT 🎬

Useful resources

Mathematical Foundations

Python and Data Science

PyTorch and Machine Learning

Open Education Statement

All notes of this class will be published in on this website under Creative Commons CC0 License. Should you wish to improve the course materials, please follow instructions here to submit issues or pull requests to this GitHub repo. This is a ZERO Textbook Cost course. Links to all materials will be accesible on this GitHub repo and website.