## Scientific Computing From Scratch

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

**Instructors**:

Yuanqing Wang (wangyq@wangyq.net), Memorial Sloan Kettering Cancer Center

Anil Zenginoglu (anil@umd.edu), University of Maryland

Onur Kara (okara83@gmail.com), Ronin Institute

Pritha Verma (pritha@mit.edu), Massachusetts Institute of Technology

Zachary Smith (zsmith7@umd.edu), University of Maryland

Rishi Bedi(rbedi100@gmail.com), Y-Trap

## Syllabus

Module | Scope | Notes | Time (Click to add to calendar) |
Video |
---|---|---|---|---|

Introduction to python | Basic syntax What is a function Useful packages Data handling Visualization |
Jun 21, 2022 4-6PM EST | ||

Your first machine learning model from scratch | Introduction to functions and objects. Implement your vector and matrix from scratch. Implement your linear regression algorithm from scratch. |
Jun 22, 2022 4-6PM EST | 🎬 | |

Numpy & Pandas | Jul 5, 2022 4-6PM EST | |||

Matplotlib & SciKit-Learn | Jul 6, 2022 4-6PM EST | |||

Introduction to machine learning with PyTorch | Basic syntax Linear regression (Stochastic) gradient descent Train a bad and a good model on MNIST |
Aug 9, 2022 4-6PM EST | 🎬 | |

Tensorboard and Convolution | Aug 10, 2022 4-6PM EST | |||

Generative Models: Alphafold and Autoencoders | Aug 23, 2022 4-6PM EST | |||

Debugging | Aug 24, 2022 4-6PM EST |

## 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.