7. Tools & Setup
The foundational toolkit for CS students. Install what you need for your direction. For lab-specific setup, also see Member Onboarding.
| Tool | Used for | Get it |
|---|---|---|
| Git & GitHub | Version control, portfolio, teamwork | https://git-scm.com/downloads · https://github.com |
| VS Code | Main editor (extensions) | https://code.visualstudio.com/ |
| Linux / WSL | Standard programming/systems environment | https://learn.microsoft.com/windows/wsl/ |
| Python environment | AI/Data/scripting (venv, pip/conda) | https://www.python.org/downloads/ |
| C/C++ build tools | DSA, systems (gcc/clang, make, CMake) | gcc/clang · https://cmake.org/ |
| Docker | Package & run consistent environments | https://www.docker.com/ |
| Database tools | SQL, schema design (DBeaver, psql) | https://dbeaver.io/ |
| LaTeX | Reports, theses, papers | https://www.latex-project.org/ · Overleaf |
| Figma | UI/UX design, wireframes | https://www.figma.com/ |
AI coding assistants​
AI coding assistants (Copilot, Claude, ChatGPT, Cursor…) speed you up but don't replace understanding.
- Good uses: explain errors, suggest structure, write tests, learn new syntax, quick review.
- Limitations: they can be wrong or "hallucinate"; you must verify and understand the code you submit.
- Academic note: follow each course's rules on AI use; many courses require you to write your own code.
Deeper setup for hardware/firmware/robotics: see Member Onboarding and the Embedded Firmware and Robotics & ROS guides.