CIS Program Description
(For students admitted before 2017 please visit)
Computer and Information Science Courses
Course code – name | Credits | Concentration |
Preparatory courses (no graduate credits)
ENGS 104 – Probability and Statistics (or equivalent) | 0 | |
CS 111 – Discrete Mathematics (or equivalent) | 0 | |
CS 120 – Introduction to Object Oriented Programming (or equivalent) | 0 | |
CS 121 – Data Structures (or equivalent) | ||
CS 130 Computer Organization (or equivalent) | 0 | |
CS 211 Introduction to Algorithms (or equivalent) | 0 |
Core courses (21 credits)
Theory of Computing | 3 | Theoretical CS |
Software Project Management | 3 | Software Engineering |
Object-Oriented Analysis and Design | 3 | Software Engineering |
Advanced Object-Oriented Programming | 3 | Software Engineering |
Advanced Statistical Modeling | 3 | Data Science |
Advanced Algorithms | 3 | Theoretical CS |
Machine Learning | 3 | Data Science |
Capstone (6 credits)
CIS Capstone Preparation (2nd year standing) | 3 | |
CIS Capstone Thesis (2nd year standing) | 3 | |
CIS Capstone Practicum (2nd year standing) | 3 |
Concentration Requirements (15 credits)
Image Processing | 3 | Theoretical CS or Data Science |
Databases | 3 | Software Engineering |
Artificial Intelligence | 3 | Data Science |
Distributed System | 3 | Software Engineering |
HP Computing | 3 | Software Engineering or Theoretical CS |
Compiler Design | 3 | Software Engineering |
Operating Systems | 3 | Software Engineering |
Entrepreneurship | 3 | Software Engineering |
Software Engineering | 3 | Software Engineering |
Advanced Cryptography | 3 | Theoretical CS |
Deep Learning | 3 | Data Science |
Network Programming | 3 | Software Engineering |
Databases | 3 | Software Engineering |
Knowledge Representation | 3 | Data Science |
Data Visualization | 3 | Data Science |
Time Series Analysis | 3 | Data Science |
Data Warehousing | 3 | Software Engineering |
Game Theory | 3 | Data Science |
Computer Graphics | 3 | Software Engineering |
Additional Electives (6 credits)
Bioinformatics | 3 | |
Data Mining & Predictive Analytics 1 | 3 | |
Quality Assurance & Management | 3 | |
Portfolio Theory | 3 | |
CAD/CAM | 3 | |
Production Systems Analysis | 3 | |
Supply Chain Management | 3 |
Graduation requirements
- All students must successfully pass the seven Core courses (21 credits). Please note that students should be aware of the Preparatory undergraduate coursework needed for their CIS graduate courses. If a student has not completed these prerequisites during their undergraduate studies, he/she should enroll in the corresponding Preparatory courses.
- Students must also choose one of three concentrations: Theoretical Computer Science (TCS), Data Science (DS), or Software Engineering (SE).
- Students choosing the TCS Concentration must successfully complete 15 credits from the Theoretical Computer Science Concentration (outside of the core).
- Students choosing the DS Concentration must successfully complete 15 credits from the Data Science Concentration (outside of the core).
- Students choosing the SE Concentration must successfully complete 15 credits from the Software Engineering Concentration (outside of the core)
- All students must complete the six-credit Capstone requirement.
- All students must complete the AUA environmental requirement (at least 1 credit), by passing for a grade any course pre-approved by the Program Chair which fulfills the requirement.
- A student must complete at least 48 credits for graduation, and all courses must be taken on a letter grade basis. A cumulative grade-point average of 3.0 or higher is required for graduation. Students who wish to register for electives not listed must get prior approval from the Program Chair.
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