ARTIFICIAL INTELLIGENCE (DS3026)

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Introduces some of the key ideas and concepts in artificial intelligence (e.g. knowledge bases, problem solving). Provides an overview of current applications (expert systems and rule-based systems, language understanding, perception, learning). Introduces some of the techniques (matching, goal reduction, tree-pruning, searching, etc.) that are typically used.

Code: 
DS3026
Name: 
ARTIFICIAL INTELLIGENCE
Discipline: 
DS (Data Science)
Type: 
Regular
Level: 
Undergraduate
Credits: 
4
Can be taken twice for credit?: 
No
Pre-requisites: 
CS2071 AND (MA2400 OR MA2400CCD)
Co-requisites: 
None
Equivalencies: 
ARTIFICIAL INTELLIGENCE (CS3026)

Learning Outcomes

  1. Will be familiar with the main paradigms in AI.
  2. Will know the best practices in the field in various domains.
  3. Will be familiar with PROLOG and LISP languages.
  4. Will be able to recognize the correct technique/tool most suitable for a given AI problem.
  5. Will know the state of the art in the field.

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