Computer Science (BS)
The Computer Science program combines a rigorous education in computer science with added coursework in an area outside of computing, in the sciences, business or humanities. With a background that combines computer science and a non-computing discipline, our graduates have the breadth of understanding to apply computer science to other disciplines, which is particularly valuable as computing has become a key aspect of nearly all endeavors.
The Computer Science undergraduate program educational objectives are that our alumni/ae: practice and grow as computing professionals, conducting research and/or leading, designing, developing or maintaining projects in various technical areas of computer science; utilize knowledge and skills in Computer Science effectively for improving the society; and use new technical advancements of Computer Science to produce tangible contributions in the profession.
The Computer Science program is accredited by the Computing Accreditation Commission of ABET, under the commission’s General Criteria and Program Criteria for Computer Science and Similarly Named Computing Programs.
Location
- Stamford Campus
- Storrs Campus
Modality
- In Person
Bachelor of Science
The Computer Science major requires a total of 120 credits.
| Course | Title | Credits |
|---|---|---|
| Required Computer Science and Engineering (CSE) Courses | ||
| CSE 1010 | Introduction to Computing for Engineers | 3 |
| CSE 2050 | Data Structures and Object-Oriented Design | 3 |
| CSE 2500 | Introduction to Discrete Systems | 3 |
| CSE 3000 | Contemporary Issues in Computer Science and Engineering | 1 |
| CSE 3100 | Systems Programming | 3 |
| CSE 3140 | Cybersecurity Lab | 2 |
| CSE 3150 | C++ Essentials | 3 |
| or CSE 3160 | Functional Programming Fundamentals | |
| CSE 3500 | Algorithms and Complexity | 3 |
| CSE 3666 | Introduction to Computer Architecture | 3 |
| CSE 4939W | Computer Science and Engineering Design Project I | 3 |
| CSE 4940 | Computer Science and Engineering Design Project II | 3 |
| Additional Required Courses | ||
| MATH 2110Q | Multivariable Calculus | 4 |
| MATH 2210Q | Applied Linear Algebra | 3 |
| Select one of the following: | 3 | |
| Probability | ||
| Statistical Methods | ||
| Probability Models for Engineers | ||
| Introduction to Mathematical Statistics I | ||
| Additional Laboratory Course Sequence | ||
| Select one two-semester laboratory course sequence from either: | 8 | |
| Chemistry | ||
| General Chemistry I and General Chemistry II | ||
| Enhanced General Chemistry I and Enhanced General Chemistry II | ||
| Honors General Chemistry I and Honors General Chemistry II | ||
| Physics | ||
| General Physics with Calculus I and General Physics with Calculus II | ||
| Physics for Engineers I and Physics for Engineers II | ||
| Fundamentals of Physics I and Fundamentals of Physics II | ||
| Additional Science Course | ||
| Select one additional science course from the following list (but not in the same department as the two semester sequence): | 4 | |
| Principles of Biology I | ||
or BIOL 1108 | Principles of Biology II | |
or BIOL 1110 | Introduction to Botany | |
| General Chemistry I | ||
or CHEM 1128Q | General Chemistry II | |
| General Physics with Calculus I | ||
or PHYS 1402Q | General Physics with Calculus II | |
or PHYS 1502Q | Physics for Engineers II | |
or PHYS 1601Q | Fundamentals of Physics I | |
or PHYS 1602Q | Fundamentals of Physics II | |
| Earth's Dynamic Environment | ||
or ERTH 1051 | Earth's Dynamic Environment (Lecture) | |
or ERTH 1052 | Earth's Dynamic Environment (Laboratory) | |
| Additional CSE Courses and Electives | ||
| Additional CSE courses as required to reach 43 credits in CSE courses | ||
| Elective courses to reach a minimum of 120 credits | ||
Concentrations
Computer Science majors may complete one of the following concentrations. Each concentration specifies a required course and a set of elective courses. To complete a concentration, students must have a C or better grade from the required course and earn additional nine credits from the elective courses in the concentration. Students who do not select a concentration must have 12 credits from 3000+ level CSE courses beyond the required CSE courses. With prior approval by the School Director, CSE 4095 Special Topics in Computer Science and Engineering and CSE 5095 Special Topics in Computer Science and Engineering, and up to 3 credits of CSE 4099 Independent Study in Computer Science and Engineering, CSE 4900 Independent Design Laboratory, or CSE 4997 Senior Thesis in Computer Science and Engineering may be included toward either of these requirements.
Algorithms and Theory
| Course | Title | Credits |
|---|---|---|
| CSE 3502 | Theory of Computation | 3 |
| or CSE 5503 | Theory of Computation | |
| Select three of the following: | 9 | |
| Numerical Methods in Scientific Computation | ||
| Programming Language Translation | ||
| Introduction to Quantum Computing, Cryptography, and Networking | ||
| Big Data Analytics | ||
or CSE 5717 | Big Data Analytics | |
| Introduction to Modern Cryptography | ||
| Introduction to Machine Learning | ||
or CSE 5819 | Introduction to Machine Learning | |
| Algorithms | ||
| Introduction to Quantum Computing | ||
| Reinforcement Learning | ||
| Modern Cryptography: Primitives and Protocols | ||
| Randomization in Computing | ||
| Total Credits | 12 | |
Artificial Intelligence
| Course | Title | Credits |
|---|---|---|
| CSE 4820 | Introduction to Machine Learning | 3 |
| or CSE 5819 | Introduction to Machine Learning | |
| Select three of the following: | 9 | |
| Big Data Analytics | ||
or CSE 5717 | Big Data Analytics | |
| Data Visualization and Communication | ||
or BADM 3302 | Data Visualization | |
| Principles of Databases | ||
| Artificial Intelligence | ||
| Computer Vision and Machine Learning for Image Analysis | ||
| Special Topics in Computer Science and Engineering (as Social Media Mining and Analysis) | ||
| Reinforcement Learning | ||
| Bayesian Machine Learning | ||
or CSE 5830 | Probabilistic Graphical Models | |
or CSE 5835 | Machine Learning for Physical Sciences and Systems | |
| Discrete Optimization | ||
or BADM 3301 | Spreadsheet Modeling for Business Analysis | |
| Data Mining | ||
| Information Ecosystem Threats | ||
| Total Credits | 12 | |
Bioinformatics
| Course | Title | Credits |
|---|---|---|
| CSE 3800 | Bioinformatics | 3 |
| or CSE 5800 | Bioinformatics | |
| Select three of the following: | 9 | |
| Computational Genomics | ||
or CSE 6800 | Computational Genomics | |
| Big Data Analytics | ||
or CSE 5717 | Big Data Analytics | |
| Introduction to Machine Learning | ||
or CSE 5819 | Introduction to Machine Learning | |
| Computer Vision and Machine Learning for Image Analysis | ||
| Introduction to Biomedical Informatics | ||
| Reinforcement Learning | ||
| Bayesian Machine Learning | ||
| Probabilistic Graphical Models | ||
| Computational Problems in Evolutionary Genomics | ||
| Total Credits | 12 | |
Cybersecurity
| Course | Title | Credits |
|---|---|---|
| CSE 3400 | Introduction to Cryptography and Cybersecurity | 3 |
| or CSE 5850 | Introduction to Cyber-Security | |
| Select three of the following: | 9 | |
| Computer Networks and Data Communication | ||
or CSE 5299 | Computer Networks and Data Communication | |
or CSE 3502 | Theory of Computation | |
or CSE 5503 | Theory of Computation | |
or CSE 4300 | Operating Systems | |
or CSE 5305 | Operating Systems | |
| Blockchain Technology | ||
| Computer Security | ||
or CSE 5400 | Computer Security | |
| Network Security | ||
or CSE 5402 | Network Security | |
| Introduction to Quantum Computing, Cryptography, and Networking | ||
or CSE 5512 | Introduction to Quantum Computing | |
| Introduction to Modern Cryptography | ||
or CSE 5852 | Modern Cryptography: Foundations | |
| Modern Cryptography: Primitives and Protocols | ||
| Information Ecosystem Threats | ||
| Total Credits | 12 | |
Software Design and Development
| Course | Title | Credits |
|---|---|---|
| CSE 2102 | Introduction to Software Engineering | 3 |
| Select three of the following: | 9 | |
| C++ Essentials 1 | ||
or CSE 3160 | Functional Programming Fundamentals | |
| Mobile Application Development | ||
| Introduction to Cloud Computing | ||
| Programming Language Translation | ||
| Programming Languages | ||
or CSE 5102 | Advanced Programming Languages | |
| Operating Systems | ||
or CSE 4701 | Principles of Databases | |
or CSE 5305 | Operating Systems | |
| Special Topics in Computer Science and Engineering (as Social Media Mining and Analysis) | ||
| Performance Engineering | ||
| Total Credits | 12 | |
- 1
That was not used to meet core requirements.
Software Design for Mobile Computing
| Course | Title | Credits |
|---|---|---|
| Mobile Application Development | ||
| Select three of the following: | 9 | |
| Introduction to Software Engineering | ||
| C++ Essentials 1 | ||
or CSE 3160 | Functional Programming Fundamentals | |
| Introduction to Cloud Computing | ||
| Computer Networks and Data Communication | ||
or CSE 5299 | Computer Networks and Data Communication | |
| Introduction to Cryptography and Cybersecurity | ||
or CSE 5850 | Introduction to Cyber-Security | |
| Big Data Analytics | ||
or CSE 5717 | Big Data Analytics | |
| Principles of Databases | ||
| Artificial Intelligence | ||
| Introduction to Machine Learning | ||
or CSE 5819 | Introduction to Machine Learning | |
| Total Credits | 9 | |
- 1
That was not used to meet core requirements.
Systems and Networks
| Course | Title | Credits |
|---|---|---|
| CSE 3000 | Contemporary Issues in Computer Science and Engineering | 3 |
| or CSE 5299 | Computer Networks and Data Communication | |
| Select three of the following: | 9 | |
| Introduction to Cloud Computing | ||
| Introduction to Cryptography and Cybersecurity | ||
or CSE 5850 | Introduction to Cyber-Security | |
| Operating Systems | ||
or CSE 5305 | Operating Systems | |
| Computer Organization and Architecture | ||
or CSE 5302 | Computer Architecture | |
| Introduction to Quantum Computing, Cryptography, and Networking | ||
| Networked Embedded Systems | ||
or CSE 5309 | Networked Embedded Systems | |
| Advanced Computer Networks | ||
| Architecture of Internet of Things | ||
| Total Credits | 12 | |
Naval Science and Technology
The concentration in Naval Science and Technology is designed to expose students to engineering concepts and topics of importance to the Navy and industries that support naval science and technology. It is focused on facilitating interactions between students and naval professionals as well as hands-on and experiential activities related to senior design projects or independent study projects that have naval science and technology connections.
All Computer Science majors must also complete nine credits of Naval Science and Technology Coursework topics, distributed as follows:
| Course | Title | Credits |
|---|---|---|
| ENGR 3109 | Navy STEM Professional Development Seminar (at least three credits) | 3 |
| Select two of the following: 1 | 6 | |
| Special Topics in Computer Science and Engineering | ||
| Independent Study in Computer Science and Engineering | ||
| Computer Science and Engineering Design Project I | ||
| Computer Science and Engineering Design Project II | ||
| Total Credits | 9 | |
- 1
With at least one course outside the senior design sequence.
Students electing to complete the concentration must do so in their primary major, and as such select elective coursework from their primary discipline. Students electing to use their Senior Design course sequence must have their project topic approved by both their departmental senior design coordinator and either the director of the Navy STEM Program or the Associate Dean for Undergraduate Education.
Students electing to use Special Topics courses or Independent Study/Research courses must have the course or research topic approved by both their department and either the director of the Navy STEM Program or the Associate Dean for Undergraduate Education. Other courses relevant to naval science and technology may be considered for the concentration by petition to the director of the Navy STEM Program or the Associate Dean of Undergraduate Education. Students may not apply courses used in this concentration to fulfill requirements for other concentrations or minors. The concentration in Naval Science and Technology is restricted to U.S. citizens.
University Common Curriculum Requirements
Every student must meet a set of core requirements to earn a baccalaureate degree, in addition to those required by the student's major course of study and other requirements set by the student's school or college. For more information about these requirements, please see Common Curriculum Requirements.
College of Engineering Degree Requirements
Students must meet a set of requirements established by the college in addition to the University's Common Curriculum requirements. For more information, see the College of Engineering section of this catalog.
Learning Objectives
- Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
- Apply computer science theory and software development fundamentals to produce computing-based solutions.