This course is aimed at research students and academics wanting to learn the fundamentals of Python and its AI capabilities. Tailored for beginners with little to no prior coding experience, the course will focus on the core Python concepts essential for data manipulation and analysis. Expect a casual pace as we explore common science data types (csv, spatial, temporal, vector, raster, etc) to demonstrate general and AI workflows. 

Participants will gain a practical understanding of:

• Python Fundamentals: Learn the basic syntax, data types (like numbers, strings, lists, and dictionaries), and control flow (loops and conditionals) in Python.
• Working with Data: Understand how to import, clean, and manipulate scientific datasets using powerful Python libraries like Pandas.
• Introduction to AI for Science: Get hands-on experience using AI in various scientific domain problems with specific examples you can replicate to your workflows.
• Setting up your Environment: Learn how to set up a AI-enabled Python environment suitable for scientific computing with Colab and Gemma.

The course will be all hands-on exercises and live coding demonstrations to reinforce your learning and build confidence.

Requirements: 

1. A Google account to use Colab for Python https://colab.research.google.com/
2. An API key from https://aistudio.google.com/apikey to use web based models.
3. A Kaggle account (you can use your Google credentials) to download AI models https://www.kaggle.com/
4. Working in a research related field at an Australian institution. Your ticket will be cancelled if this cannot be verified.

Course will be delivered virtually over Google Meet for 4 hours with plenty of breaks.