AI assisted scientific programming in Python

Syllabus:

This is a hands-on course. During the course the participants will install software on their computer and will develop software on their computer.

• Version control using git and GitHub.
• The basics of Markdown to write documentation, interact with AI systems, etc.
• Creating a web page using HTML and CSS for displaying results.
• Using JupyterLab for interactive data analysis.
• Using an IDE for local development (VS Code or PyCharm)
• Using AI systems for development:
  • OpenAI: ChatGPT + Codex
  • Google: Gemini + Antigravity
  • Anthropic: Claude Code
  • Microsoft (GitHub): co-pilot.
• Implementing mathematical (statistical) computation.
• Creating a command line application.
• Dividing the code into core scientific logic and user interaction.
• Testing the results of our computations.
• Selecting and using 3rd-party libraries.
• Analyzing tabular data from an Excel or CSV file.
• Machine learning to analyze data and create predictions.
• Generating graphs from the data.
• Creating a desktop application (GUI) for easy interaction with the core scientific logic.
• Creating a web application to interact with the core scientific logic.