Course overview
The aim of this course is to develop and deploy Artificial Intelligence and Machine Learning Systems. Introduction to artificial intelligence; apply machine learning algorithms for classification and regression; search-based problem solving: heuristic search (A*, perhaps Planning); constraint satisfaction / optimisation; evolutionary algorithms; adversarial search / stochastic methods MCTS (Alpha Zero); nature of ML methods; supervised learning, data preparation, training; validation, overfitting; computer vision; tools and deployment; applications in Natural Language Processing; embedding AI systems in the real world / ethics / problems.
Course learning outcomes
- Discuss the capabilities and limitations of AI and ML systems
- Solve intractable problems using search based problem solving techniques
- Apply the principles of data preparation, training, and validation techniques for ML
- Utilise methods for interfacing with real world environments
- Describe the ethical implications related to AI systems