Course

Objective:

Learning Outcomes:

• explain the foundations, history and ethical perspectives of artificial intelligence, and the science of agent design
• illustrate the use of problem-solving techniques, such as the various search methods, gaming and self-learning agents
• demonstrate AI's use of knowledge representation, through logic agents and first-order logic to address AI problems
• discuss the philosophical foundations of AI and explain the possibilities for the future of AI
• recognize the different types of artificial intelligent systems in use today and how they are affecting our lives
• distinguish machine code and higher-level computer languages, how they are interpreted and compiled
• define computer security risks, explain how to prevent security breaks and maintain protection
• analyze algorithms and intelligent programs, write pseudocode and intelligent agents
• design decision tree algorithms for data mining using Markov processes, localization, slam and lisp
• create neural networks to include image processing, reasoning, and advanced planning

General Topics: