Lecturer
Dr Alina Donea, Monash University
Synopsis
This 4-week course on Data Science and AI has a solid foundation in mathematics and algorithms that should balance theory, practice, and real-world application
Course Overview
TBA
Prerequisites
- Tools/Frameworks to Use Along the Way:
- Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow)
- Jupyter Notebooks
- Git/GitHub
- VS Code
Assessment
- Assignments – 45%
- 2 Mathematics tasks
- 2 Python/AI coding tasks
- GitHub & Presentation – 5%
- Upload code, data, and create a webpage for your work
- Team Leadership – 5%
- Help design and coordinate workshop tasks for peers
- Use of AI Tools – 15%
- Apply ChatGPT or similar tools to solve mathematical problems in AI. demonstrate how AI tools like ChatGPT can be used in real-time to support mathematics and coding for AI applications. Reflection and Evaluation.
- Final Project – 30%
- A full end-to-end project showcasing your skills
Resources/pre-reading
Not sure if you should sign up for this course?
Take this pre-enrolment QUIZ to self-evaluate and get a measure of the key foundational knowledge required. NOTE: this is a google drive link containing a Jupyter python notebook.