Course Project

This course is designed to introduce mathematicians and scientific computing students to essential software development tools and practices. No prior programming or Linux experience required.

Difficulty Levels

Each topic is organized by difficulty level:

🟢 FOUNDATIONAL

Prerequisites: None

Essential tools every mathematician needs for computational work

🟡 INTERMEDIATE

Prerequisites: Linux basics, Git fundamentals

Collaborative development and project management

🔴 ADVANCED

Prerequisites: All previous modules

High-performance computing and automation

Course Topics

🐧 Linux

Master command-line essentials for mathematical computing.

🟢 Fundamentals	Shell basics, file operations, text processing
🟡 Remote Computing	SSH, remote access, VS Code Remote-SSH

→ Start Learning Linux

🔀 Git & GitHub

Track changes in LaTeX documents and collaborate on research projects.

🟢 Git Basics	Version control fundamentals, repository management
🟢 GitHub Basics	Essentials, issues, getting started
🟡 Collaboration	Branching, merging, pull requests
🔴 Automation	GitHub Actions, CI/CD workflows

→ Start Learning Git

💻 VS Code

Set up your integrated development environment for mathematical work.

🟢 Getting Started

Installation, basic usage, extensions, configuration

→ Start Learning VS Code

📓 Jupyter Notebooks

Interactive computing for mathematical research and teaching.

→ Start Learning Jupyter

📦 Containers

Create reproducible environments for mathematical computing.

🟡 Docker Fundamentals	Containers, images, Dockerfile, Docker Compose
🔴 HPC Containers	Apptainer/Singularity, HPC deployment

→ Start Learning Containers

📋 Project Management

Apply project management to mathematical research and thesis projects.

🟡 Fundamentals	Project phases, practical examples
🟡 Tools & Methods	Gantt charts, Agile practices, GitHub integration

→ Start Learning Project Management

🔄 CI/CD

Automate testing, building, and deployment of mathematical software.

🔴 Platforms

GitLab CI/CD, GitHub Actions

→ Start Learning CI/CD

📊 Visualization

Create interactive visualizations for research results.

🔴 Web Dashboards

Dash, Plotly

→ Start Learning Visualization

Quick Start

🎯 Students

Don’t jump straight into modules! Start with the Prerequisites & Self-Assessment to find your optimal starting point.

💨 In a hurry? → 🚀 Quick Start Guide

👩‍🏫 Instructors

Check out the 📚 Instructor Guide with week-by-week curriculum, assessment strategies, and teaching tips.

Questions? Join us on Slack