Algorithms on AI (SOON)

The goal is not to memorise a catalogue of algorithms but to develop a strong intuition for computational complexity, data structures, and algorithmic paradigms. The course will consistently bridge theoretical concepts to their practical applications in the AI/ML domain, answering the question, “Why does this matter for a data scientist?”

Course Outline

Algorithmic Foundations

Lecture 1. Measuring performance & complexity
Lecture 2. Foundational paradigms: search & sort

Data-centric Structures

Lecture 3. Hashing & Dictionaries
Lecture 4. Trees & Hierarchical Data
Lecture 5. Heaps & Priority Queues

Graph & Network Algorithms

Lecture 6. Graph representation & traversal
Lecture 7. Shortest Path Algorithms
Lecture 8. Minimum spanning trees (MST)

Advanced Paradigms

Lecture 9. Recursion, Backtracking, and Memoization
Lecture 10. Dynamic Programming
Lecture 11. Greedy Algorithms
Lecture 12. An algorithmic perspective on Machine Learning