From Equations to Intelligence: A Deep Dive into Data Science and AI

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

TBA

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.

Dr Alina Donea, Monash University