Course curriculum

  • 1

    Welcome to the course!

    • Welcome

    • Professors

    • Introduction

    • Schedule

    • Where you are - Quantum Mile

    • How to use this course

    • Google Colab link
  • 2

    Module 1: Intro to ML & AI

    • A Brief History of AI

    • Fundamentals of ML and AI

    • Machine Learning vs. Artificial Intelligence

    • Questionary I

    • Generative vs Predictive AI

    • Questionary II

    • Short Assignment (30 minutes): Exploring Machine Learning with NotebookLM

    • Intro to Python

    • Python Cheat Sheet

    • Set of Exercises
  • 3

    Module 2: Supervised Learning Algorithms

    • Supervised Learning - Regression

    • Supervised Learning - Classification

    • Gitlab Repository

    • Task: ML problem selection
  • 4

    Module 3: Unsupervised Learning Algorithms

    • Unsupervised Learning

    • Model Tracking with MLFlow

    • Task: ML Pipeline Results and MLFlow Implementation
  • 5

    Module 4: Deep Learning Fundamentals

    • Deep Learning Fundamentals

    • Hands on sessions

    • Task: Machine Learning vs Deep Learning comparison
  • 6

    Module 5: AI Applications

    • AI Applications

    • Hands on sessions
  • 7

    Module 7: Module 7: Course Challenge based on Project-based Learning

    • AI Application code

    • Project Presentation

    • Ethics on ML and AI
  • 8

    Next steps

    • Course Retrospective

    • Safisfaction questionary