Scientific Computing From Scratch
A summer bootcamp on scientific computing for beginners with Python and Pytorch organized by Pratyush Tiwary, University of Maryland. All classes via zoom 4-6PM New York time. Zoom link has been sent to registered students.
2024 Instructors:
João Rodrigues, Schrödinger
Eric Beyerle, University of Maryland
Ricardo Ramirez, University at Buffalo
Payam Kelich, University of Illinois Urbana-Champaign
Qianyu Zheng, Georgia Institute of Technology
Aram Bughdaryan, Deep Origin
Raunak Dey, University of Maryland
Wenhao Gao, MIT
Syllabus
| Module | Scope | Notes | Time (Click to add to calendar) |
Video |
|---|---|---|---|---|
| Introduction to python | Basic syntax What is a function Useful packages Data handling |
 |
July 10 2024 4-6PM EDT | 🎬 |
| Numpy & Data Handling | More on lists, dictionaries, arrays Data Handling with Numpy |
|
July 11 2024 4-6PM EDT | 🎬 |
| Matplotlib | Basics of Matplotlib Line plots Visualizing errors Multiple subplots Contour plots |
|
July 17 2024 4-6PM EDT | 🎬 |
| Pandas and sklearn | Working with datasets | |
July 18 2024 4-6PM EDT | 🎬 |
| Introduction to machine learning with PyTorch | Part 1 | |
July 24 2024 4-6PM EDT | 🎬 |
| Introduction to machine learning with PyTorch | Part 2 | |
July 25 2024 4-6PM EDT | 🎬 |
| More on machine learning with PyTorch | Part 1 | |
August 7 2024 4-6PM EDT | 🎬 |
| More on machine learning with PyTorch | Part 2 | |
August 8 2024 4-6PM EDT | 🎬 |
Useful resources
Mathematical Foundations
- Fun with functions playlist 🍿(4 modules of average 15 min duration)
- Single variable calculus playlist 🍿 (8 modules of average 15 min duration)
- Multi variable calculus playlist 🍿 (5 modules of average 16 min duration)
- Essence of linear algebra by 3Blue1Brown
- Essence of calculus by 3Blue1Brown
- Linear algebra (Khan Academy)
Python and Data Science
- MolSSI Education Resources
- PY4E - Python for Everybody
- Learn Python - Code Academy
- Python Documentation
- Python and Jupyter Notebooks
- Python basics notebooks
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.