Course Description

This second module builds on the foundational VS Code skills covered in Part 1. Participants will learn how to manage advanced environments and automate workflows on HPC clusters. The module also introduces language-model–assisted research, including both cloud-based tools and privacy-preserving local LLMs, to improve coding efficiency and reproducibility.

Course Requirements

To participate in this training, participants should have:

1. Basic knowledge of writing simple Python or R scripts.
2. A laptop with VS Code and Python/R installed.
3. Ability to install VS Code extensions
4. Ability or willingness to work with terminal/command line.
5. A Habrok account (more info here). It is also recommended that the participant should have completed the first part of the training or have knowledge of part 1.

Learning Objectives

1. Recap of Part 1
   • Quick review of VS Code basics, environment management, extensions, Git integration, and workflow best practices.
2. Remote Execution on HPC
   • Connect to the university HPC cluster via SSH or port forwarding.
   • Run Python and R scripts and notebooks remotely from VS Code.
   • Understand the difference between local and remote execution for reproducibility.
3. Reproducible Environments on HPC
   • Create and manage Python (venv/conda) and R (renv) environments on HPC.
   • Document and share environment configurations to ensure reproducibility.
4. Language-Model Assisted Research
   • Introduction to GitHub Copilot for Python and R.
   • Write functions using Copilot: autocomplete vs chat mode.
   • Use cloud-based LLMs or APIs for code suggestions.
   • Explore local/open-source LLMs for privacy-preserving code assistance.
      

Location: CIT Smitsborg, Zernike Campus, room: Zebra, 0017