Artificial Intelligence Tutorial
This course covers the vast field of Artificial Intelligence (AI).
As I covered when discussing my AI experience (see AI), I consider "intelligence" to be a broad term, describing any algorithm or system in which simple rules or instructions result in some surprising, complex or desirable outcome/behaviour.
For this reason, I cover all of the four main schools of AI:
- Traditional AI - for the purposes of this course, this includes anything that can be considered AI but is not ML (symbolic AI, genetic algorithms, etc.).
- Supervised Learning - the subfield of machine learning where the goal is to learn from labeled data in order to predict future outcomes.
- Unsupervised Learning - the subfield of machine learning where the goal is to analyse unlabeled data in order to understand its substructure and possibly generate new data.
- Reinforcement Learning - the subfield of machine learning where the goal is to learn from interactions with a simulated environment in order to optimise long-term goal-driven behaviour.