Machine Learning Advanced Learning Path - MAI4CAREU Master in AI

This Machine Learning (ML) learning path offers a structured curriculum that delves into the subfield of artificial intelligence that has revolutionised society, technology, and industry – and is poised to shape our future even more profoundly. It is based on the introductory course offered at the Master in Artificial Intelligence of the University of Cyprus, which was developed with co-funding from the MAI4CAREU European project.

The course offers a guided exploration of ML’s fundamental principles and diverse applications, and consists of eighteen units organised in four parts as shown below, which are further arranged into Introductory (seven units) and Advanced (eleven units) according to their level of difficulty.

The recommended order for studying all materials is the one shown below (from 1 to 18).

Part I: Introduction
     1. Introduction to Machine Learning
     2. Data Preparation

Part II: Supervised Learning
     3. Regression
     4. Classification
     5. Model Evaluation and Improvement
     6. Trees and Forests
     7. Kernel-based Methods 1
     8. Kernel-based Methods 2
     9. Neural Networks 1: Modelling
    10. Neural Networks 2: Training
    11. Neural Networks 3: Introduction to Deep Learning

Part III: Unsupervised Learning
    12. Clustering
    13. Dimensionality Reduction
    14. Anomaly Detection
    15. Recommender Systems

Part IV: Reinforcement Learning
    16. Introduction to Reinforcement Learning
    17. Markov Decision Processes and Dynamic Programming
    18. Model-free Reinforcement Learning