Artificial Intelligence, Certificate
Learning Outcome
- Students will use AI techniques or create AI tools for heuristic problem solving, automated reasoning and knowledge representation, including search algorithms, constraint processing systems, propositional theorem provers, neural networks, and probabilistic graphical models.
Admissions
Requirements for admission to all graduate degree programs in computer science and engineering include the general admission requirements of The Graduate School as well as more stringent departmental requirements, as described below. In general, the admission process is highly competitive. Admissions decisions are based on the quality of the applicant’s previous university-level academic work, letters of recommendation, GRE scores, and other evidence of past accomplishments.
For admission to the Certificate of Graduate Study program, applicants normally hold the B.S. in degree in computer science, computer engineering, or a related filed. In addition, they must have completed courses in data structures and algorithms, operating systems, database management systems, discrete mathematics, linear algebra, and probability and statistics. Students enrolled in other graduate degree programs at USC are automatically eligible to pursue the certificate as long as they have taken the prerequisite courses.
In addition, all applicants should submit an official transcript from each school or college previously attended, and at least two letters of recommendation. The admission committee will evaluate all aspects of each application and will make a recommendation on admission to The Graduate School. For full consideration, all application materials must be received by February 1 for fall and summer admission and by October 1 for spring admission.
The graduate certificate program in Artificial Intelligence requires at least 12 hours of graduate study, at least half of which must be courses at the 700-level or above with the CSCE designator, completed within a period of six years before the award of the certificate. The Certificate requires a Core Course, followed by the opportunity for a concentration to be chosen by the student in consultation with their advisor and the graduate director of the Department of Computer Science and Engineering. Example concentrations include knowledge representation and reasoning, computer vision, natural language processing, reasoning under uncertainty, and machine learning.
Degree Requirements (12 Hours)
| Course | Title | Credits |
|---|---|---|
| Core Course: | 3 | |
| Artificial Intelligence | ||
| The following courses may be used to satisfy this requirement: 1 | 9 | |
| Bayesian Networks and Decision Graphs | ||
| Big Data Analytics | ||
| Pattern Recognition and Classification | ||
| Computer Processing of Natural Language | ||
| Robotics Systems | ||
| Knowledge Representation | ||
| Data Mining and Warehousing | ||
| Machine Learning | ||
Other courses as approved by the advisor and graduate director | ||
| Total Credit Hours | 12 | |
- 1
At least 9 hours of additional courses must be selected with the approval of the advisor and graduate director. Up to 6 hours of appropriate courses may be taken from other departments and/or by transfer credit.