Difference between revisions of "CMSC421 - Introduction to Artificial Intelligence"
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Areas and issues in artificial intelligence, including search, inference, knowledge representation, learning, vision, natural languages, expert systems, robotics. Implementation and application of programming languages (e.g. LISP, PROLOG, SMALLTALK), programming techniques (e.g. pattern matching, discrimination networks) and control structures (e.g. agendas, data dependencies). | Areas and issues in artificial intelligence, including search, inference, knowledge representation, learning, vision, natural languages, expert systems, robotics. Implementation and application of programming languages (e.g. LISP, PROLOG, SMALLTALK), programming techniques (e.g. pattern matching, discrimination networks) and control structures (e.g. agendas, data dependencies). | ||
Revision as of 13:33, 2 October 2016
Course Information
Areas and issues in artificial intelligence, including search, inference, knowledge representation, learning, vision, natural languages, expert systems, robotics. Implementation and application of programming languages (e.g. LISP, PROLOG, SMALLTALK), programming techniques (e.g. pattern matching, discrimination networks) and control structures (e.g. agendas, data dependencies).
| Instructor | Section | Day & Time | Location |
|---|---|---|---|
| Donald Perlis | 0101 | MW 5:00PM - 6:15PM | CSI 3117 |
Course Prerequisite(s)
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Class Webpage
Hours Per Week
4-6 Hours p/Week
Languages Used
Python
Recommended Prior Experience
Projects, Exams, or other Assessments
Misc Info
