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Week 1: Introduction
Week 1: Introduction
A conceptual chapter on the fundamentals of AI — from exploring what qualifies as AI technology and its rich developmental history.
Week 2: Symbolic logic and logic neural networks
Week 2: Symbolic logic and logic neural networks
A study of several types of general logic (cause and effect) and introduction to a new type of neural network.
Week 3: Knowledge representation
Week 3: Knowledge representation
An exploration of methods AI can use to interact with organized data and learn from them to perform specialized tasks.
Week 5: Handling of ambiguous data
Week 5: Handling of ambiguous data
A brief swim into essential items for systems to deal with non-Boolean truths. Includes concepts such as soft computing, regular Bayes' theorem and Naïve Bayes' classifier, and fuzzy set theory and its components.
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