Accelerated Graduate Pathway code: NDAG16
Russ College of Engineering and Technology
Electrical Engineering and Computer Science, School of
Stocker Center 171
Athens, OH 45701
740.593.1492
www.ohio.edu/engineering/eecs
Avinash Karanth, Department Chair
karanth@ohio.edu
Program Overview
The Accelerated Graduate Pathway: Computer Science provides outstanding graduate students in Computer Science and Artificial Intelligence the opportunity to make simultaneous progress towards both the Bachelor of Science in Computer Science or the Bachelor of Science in Artificial Intelligence and a graduate degree in engineering. Undergraduate students admitted to the Pathway can take up to 16 credit hours of coursework towards a graduate degree, applying up to 9 credit hours of specified coursework towards the Bachelor of Science as well. Computer Science and Artificial Intelligence undergraduates commonly use this pathway to complete some coursework towards the Master of Science in Computer Science (MS Thesis track or MS Non-Thesis track) or the Doctor of Philosophy: Specialization in Computer Science while enrolled as undergraduates.
Admissions Information
Computer Science students (BS7241) will be eligible to apply for conditional admission to the AGP after completing 64.5 credit hours; students will be eligible to enroll in courses after completing 80.5 credit hours of courses in the EECS curriculum.
Artificial Intelligence students (BS7477) will be eligible to apply for conditional admission to the AGP after completing 62 credit hours; students will be eligible to enroll in courses after completing 75.5 credit hours of courses in the EECS curriculum.
Application is limited to students who:
1. Are in the Computer Science (BS7241) program or in the Artificial Intelligence (BS7477) program.
2. Have completed the first 6 semesters of the BS program curriculum, including:
- BSCS students (BS7241) must achieve a (C) grade or better in all of the required junior-level CS courses, which consist of CS3000 (Introduction to Discrete Structures), CS3200 (Organization of Programming Languages), CS3620 (Database System), CS3610 (Data Structures), CS3560 (Software Engineering Tools and Practices), EE3613 (Computer Organization), EE3713 (Applied Probability and Statistics for Electrical Engineers), and MATH3200/3210 (Linear Algebra); however no more than six (6) semester hours of grades at B-, C+, or C may be applied toward EEMS degree requirements.
- BSAI students (BS7477) must achieve a (C) grade or better in all of the required junior-level AI courses, which consist of MATH3200 (Linear Algebra), CS3000 (Introduction to Discrete Structures), EE3713 (Applied Probability and Statistics for Electrical Engineers), CS3200 (Organization of Programming Languages), CS3560 (Software Engineering Tools and Practices), CS3610 (Data Structures), EE3613 (Computer Organization), AI3100 (Foundations of Artificial Intelligence), and AI3300 (Statistical Learning); however no more than six (6) semester hours of grades at B-, C+, or C may be applied toward EEMS degree requirements.
3. Have a cumulative GPA of at least 3.25 or a minimum GPA of 3.0 overall with 3.5 in the most recent 30 hours.
Opportunities Upon Graduation
As this program is specifically designed to allow students to take courses towards a graduate degree while enrolled as an undergraduate student, the expectation is that students will enroll in a graduate degree program after completing the Bachelor of Science. The Accelerated Graduate Pathway: Computer Science facilitates more rapid completion of the Master of Science in Computer Science or the Doctor of Philosophy: Specialization in Computer Science. A student who takes full advantage of the pathway can typically complete the Master of Science in Computer Science (MS Thesis track or MS Non-Thesis track) within one year after completing their Bachelor of Science.
Students may leave the AGP with a BSCS or BSAI degree and not complete the MS degree, if they choose to do so, without any consequences. They will be awarded an accredited BS degree, and when they leave with a BS degree, they will have the same preparation and all the same career options as regular BS graduates. They can also leave the AGP during their BSCS or BSAI degree without consequences. Any graduate-level course they complete will count toward their BS degree as an elective.
Requirements
Students may complete up to 16 hours of graduate-level coursework under the AGP; however, only three graduate courses for a maximum of 9 credit hours will be counted toward the respective BS programs.
There are several dual-listed Technical Elective courses. Any graduate version of a course on the Technical Elective list can be used to count as a Technical Elective in the undergraduate degree requirements.
Students in the AGP involving BSCS must complete nine courses from the following list or their graduate 5XXX/6XXX version when available. Other CS courses may be used with department approval.
- CS 4060 / CS5060 Computation Theory (3 credits)
- CS 4120 Parallel Computing I (3 credits)
- CS 4150 / CS5150 Data Science: Algorithms, Processes, and Applications (3 credits)
- CS 4160 /CS5160 Problem Solving with Bioinformatics Tools (3 credits)
- CS 4170 / CS5170 Data Mining With Applications in Life Sciences (3 credits)
- CS 4180 / CS5180 Statistical Foundation for Bioinformatics (3 credits)
- CS 4201 / CS5201 Software Verification (3 credits)
- CS 4350 / CS5350 Fundamentals of Game Engine Design (3 credits)
- CS 4440 / CS5440 Data Communications (3 credits)
- CS 4580 / CS5580 Operating Systems II (3 credits)
- CS 4750 / CS5750 Internet Engineering (3 credits)
- CS 4770 / CS5770 Introduction to Computer Software Security for Engineering (3 credits)
- CS 4830 /CS5830 Machine Learning (3 credits)
- EE 4673 / EE5673 Embedded Systems (3 credits)
- EE 4683 / EE5683 Computer Architecture (3 credits)
- EE 4773 / EE5773 Foundations of Hardware Security (3 credits)
Elective courses students in the AGP may select from with department approval.
- BME 5170 Data Mining with Applications in Life Sciences (3 credits)
- CS 5000D Introduction to Discrete Structures (3 credits)
- CS 5150 Data Science
- CS 5160 Problem Solving with Bioinformatics Tools (3 credits)
- CS 5170 Data Mining with Applications in Life Sciences (3 credits)
- CS 5180 Statistical Foundation for Bioinformatics (3 credits)
- CS 5200D Organization of Programming Languages (3 credits)
- CS 5201 Software Verification (3 credits)
- CS 5350 Fundamentals of Game Engine Design
- CS 5420 Operating Systems (3 credits)
- CS 5440 Data Communications (3 credits)
- CS 5580 Operating Systems II (3 credits)
- CS 5610D Data Structures (3 credits)
- CS5750 Internet Engineering (3 credits)
- CS5770 Introduction to Computer Software Security for Engineering (3 credits)
- CS 5800 Artificial Intelligence (3 credits) CS 5830 Machine Learning (3 credits)
- CS 5880 Game AI
- CS 6040 Advanced Algorithms (3 credits)
- CS 6050 Parallel Computation Theory (3 credits)
- CS 6060 Computational Complexity (3 credits)
- CS 6120 Real-Time Systems (3 credits)
- CS 6150 Computational Genomics (3 credits)
- CS 6250 Computer Graphics and Visualization (3 credits)
- CS 6410 Medical Image Analysis (3 credits)
- CS 6420 Artificial Intelligence in Medicine (3 credits)
- CS 6440 Advanced Topics in Computer Networking (3 credits)
- CS 6571 Software Specification (3 credits)
- CS 6572 Software Design (3 credits)
- CS 6573 Software Implementation (3 credits)
- CS 6800 Advanced Topics in Artificial Intelligence (3 credits)
- CS 6820 Artificial Intelligence: Case-Based Reasoning (3 credits)
- CS 6840 Natural Language Processing (3 credits)
- CS 6850 Computer Vision (3 credits)
- CS 6860 Information Retrieval and Web Search (3 credits)
- CS 6890 Deep Learning (3 credits)
- EE 6633 Architecture of Parallel Computers (3 credits)
- EE 6663 Pattern Recognition (3 credits)
- EE 6673 Interconnection Networks for High-Performance Computing Systems (3 credits)
- EE 6743 Information Theory (3 credits)
Students in the AGP involving BSAI must complete four courses from the following list or their graduate 5XXX/6XXX version when available:
- CS 4150 / CS5150 Data Science: Algorithms, Processes and Applications) (3 credits)
- CS 4160 / CS5160 Problem Solving with Bioinformatics Tools (3 credits)
- CS 4170 / CS5170 Data Mining with Applications in Life Sciences (3 credits)
- CS 4420 / CS5420 Operating Systems (3 credits)
- CS 4830 / CS5830 Machine Learning (3 credits)
- Any 4XXX / 5XXX-level AI course EXCEPT AI 4900 (3 credits)
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