Introductory Courses
No Introductory Course may be substituted for any other course at any level.
Introductory courses may be waived for any of the following conditions:
- The student has the appropriate course work to satisfy an Introductory Course.
- The student has appropriate and verified professional experience to satisfy an Introductory Course.
- If an exam is available, the student passes a
Graduate Assessment Examination (GAE) in the Introductory Course area.
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CSC 400 Discrete Structures for Computer Science
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CSC 401 Introduction to Programming
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CSC 402 Data Structures I
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CSC 403 Data Structures II
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CSC 412 Tools and Techniques for Computational Analysis
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IT 403 Statistics and Data Analysis
Required Courses
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CSC 421 Applied Algorithms and Structures
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CSC 480 Artificial Intelligence I
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CSC 484 Ethics in Artificial Intelligence
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CSC 578 Neural Networks and Deep Learning
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CSC 580 Artificial Intelligence II
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CSC 583 Natural Language Processing
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CSC 587 Cognitive Science
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DSC 540 Advanced Machine Learning
Major Electives
Choose eight (8) credits from the following list:
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CMNS 549 Special Topics in Organizational Communication
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CSC 458 Symbolic Programming
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CSC 481 Introduction to Image Processing
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CSC 482 Applied Image Analysis
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CSC 528 Computer Vision
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CSC 555 Mining Big Data
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CSC 575 Intelligent Information Retrieval
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CSC 577 Recommender Systems
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CSC 594 Topics in Artificial Intelligence
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CSE 475 Introduction to Robotics (Formerly CSC 475)
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CSEC 440 Information Security Management
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DSC 450 Database Processing for Large-Scale Analytics
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DSC 478 Programming Machine Learning Applications
- DSC 480 Social Network Analysis
- SE 488 Ai-Driven Software Development
- SE 489 Machine Learning Engineering for Production (Mlops)
Open Electives
Student must complete four (4) credits of advisor-approved graduate courses from the School of Computing in the range of 421-699. Students may select from the following subjects: CSC, CSE, CSEC, DSC, ECT, GAM, HIT, IS, IT, NET, SE.
Capstone Requirement
Choose one courses from the following list:
The internship option offers students the opportunity to integrate their academic experience with on-the-job training on an AI-related project. Students must enroll in CSC 697 for 4 credit hours to satisfy the capstone requirement. These are the steps: 1) Secure an internship with focus in AI. 2) International Students must obtain the appropriate practical training form and meet with an advisor in the CDM Academic Center for approval. ISS Forms 3) Login to MyCDM and click the “Internships” link on the left to start the course enrollment process.
A student who is working on a research project and has made an original contribution to their area of study may choose to complete a Master's Thesis. Additional information and requirements for School of Computing students pursuing the thesis option can be found on the SoC Master's Thesis Guideline page