- artificial intelligence - definition, scope, successes and limitations.
- Logic, propositional calculus, predicate calculus, inference; fuzzy logic; logical programming, PROLOG.
- Expert Systems, knowledge, domains, rules, inference engine, forward and backward chaining, tree searching, probability and certainty, combining fuzzy facts, apriori probability, applications.
- Information retrieval and disambiguation.
- Introduction to pattern recognition and neural networks.
- Linguistics, grammar, surface structure, deep structure, structure representations, transformations, lexical decomposition, n-gram models, classification, domains.
- Speech recognition.
- Knowledge and understanding of techniques and selected software relevant to the field of artificial intelligence.
- Ability to identify techniques relevant to particular problems in artificial intelligence.
- Ability to discuss and provide proofs for basic rules used in artificial intelligence.
- Ability to identify opportunities for software solutions.
- Ability to interrogate a knowledge base in PROLOG.
- Ability to understand and use natural language grammars.
- Ability to solve specific problems using the rules of artificial intelligence e.g. in pattern recognition.
Analysis of problems, design of solutions, application of techniques, understanding results.