香港伦理

Master of Science in Computer Science

Program Purpose

The Computer Science field is among the fastest-growing fields in the United States. 香港伦理's MS in Computer Science curriculum is designed to align with high-demand emerging areas of computing. Students will be equipped with the skills to handle complex real-world computing challenges to become data scientists or software engineering professionals. The curriculum will cover topics focused on data structure and algorithms, Python programming, intro to data science, principles of software engineering, ethics in digital world, theories in artificial intelligence, cloud-based machine learning, deep learning and neural networks, natural language processing, data mining, data analytics, software engineering methodologies, software system requirements, usability engineering, information system architecture, DevOps, project management, and a final capstone course.

The MS in Computer Science program prepares students for a variety of job opportunities such as: computer scientist, computer and information systems managers, computer and information researcher, computer programmers, computer science teachers, software developers, information security analysts, database administrators, computer systems analysts, computer systems administrators, software engineers, data scientists, etc.

The 30-credit MS in Computer Science program includes two concentrations that align with industry and workforce needs and provide students focused learning and dynamic skill sets:

a. MS Computer Science - Artificial Intelligence

b. MS Computer Science - Software Engineering

The MS in Computer Science consists of 6 credits of core courses, 18-21 credits of concentration courses, and 3-6 credits of elective courses.

Durable and Technical Skills

The MS in Computer Science program provides students with technical skill and a wide range of durable skills. Students will gain a deep understanding of programming languages, algorithms, and data structures, forming the graduate's technical expertise bedrock, measured by the program competencies. Equally important, students develop critical thinking and problem-solving abilities that are invaluable when addressing real-world problems. They will learn to analyze issues methodically, break them into smaller, manageable components, and devise efficient solutions. MS in Computer Science courses also emphasize collaboration and communication, honing students' capacity to work in dynamic teams, develop and communicate their ideas effectively, and present information in accessible ways. These are essential skills for success in any professional setting. The graduation competencies will measure the durable skills learned throughout the MS in Computer Science program.

The MS in Computer Science program will also encourage adaptability and a continuous learning mindset, which is crucial in a rapidly evolving field like computer science. Students become adept at quickly mastering new technologies and methodologies, enabling them to stay abreast of emerging trends and innovations. As the computer science field continues to evolve, graduates will need a strong foundation in ethical considerations, understanding the implications and responsibilities of developing and implementing technological solutions. The combination of technical and durable skills provides a pathway to success for any MS in Computer Science graduate.

Program Competencies

In addition to satisfying the University's graduate graduation competencies, students will have an advanced level of applicable knowledge in the following areas as appropriate to one's field of study.

Computer Science – Artificial Intelligence Concentration

1. Analyze the requirements, scope, and impact of Computer Science concepts effectively and professionally.
2. Apply computer science best practices and current methodologies to create, deliver, and support computer science projects and their importance to practical problems.
3. Evaluate implementation of various models of Machine Learning within a modern organization.
4. Analyze and evaluate scenarios for implementing Deep Learning systems in an organization.

Computer Science – Software Engineering Concentration

1. Analyze the requirements, scope, and impact of Computer Science concepts effectively and professionally.
2. Apply computer science best practices and current methodologies to create, deliver, and support computer science projects and their importance to practical problems.
3. Apply Usability Engineering/Human-Computer Interaction best practices to a scenario.
4. Develop an Information Systems Architecture plan for a modern organization. 

Concentration in Artificial Intelligence (30 credits)

Students in the MS: Computer Science - Artificial Intelligence concentration will complete two courses from the Computer Science core (6 credits), seven courses for the concentration (21 credits), and choose one elective (3 credits) for a total of 30 credits.

Computer Science Core Courses

Ethics in Digital World

CSC Capstone Project

Artificial Intelligence Concentration Courses

Python Programming

Theory of Artificial Intelligence

Cloud-Based Machine Learning

Deep Learning and Neural Network

Natural Language Processing (NLP)

Large Language Models and RAG

Mathematics for Machine Learning

Choose one of the following three courses:

Agentic AI and Multi-Agent Systems

Computer Vision

Reinforcement Learning

Concentration in Software Engineering (30 credits)

Students in the MS Computer Science - Software Engineering concentration will complete the two courses from the Computer Science core (6 credits), the concentration (18 credits), and two electives (6 credits) for a total of 30 credits.

Computer Science Core Courses

Ethics in Digital World

CSC Capstone Project

Software Engineering Concentration Courses

Algorithms and Advanced Data Structures

Software Engineering Methodologies

Software Systems Requirements

Usability Engineering/Human-Computer Interaction

Information Systems Architecture

DevOps

Select two of the following three courses:

Agile Project Management

Project and Change Management

Cloud Management

This information applies to students who enter this degree program during the 2026-2027 Academic Year. If you entered this degree program before the Fall 202 semester, please refer to the academic catalog for the year you began your degree program.