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Computer Science, Master of Science

 


Program Purpose

The Computer Science field is among the fastest-growing fields in the United States. Wilmington University MS 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, become data scientists or software engineering professionals. The MS Computer Science 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 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 scientist, etc.

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

a.           MS Computer Science - Data Science

b.           MS Computer Science - Software Engineering

The MS-Computer Science core consists of 15 credits of core courses focusing on algorithms and data structures, Python programming, intro to data science or intro to software engineering, and ethics in the digital world, culminating in a Capstone Project. Students will complete the MS-Computer Science core and 15 credits of courses in the student’s selected field of concentration.

Durable and Technical Skills

The MS Computer Science program provides students with not only technical skill but also 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 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 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 Computer Science graduate.

Program Prerequisites

Students without a computer science or technology undergraduate degree will complete the program prerequisites (12 credits) to obtain the fundamental computer science skills which are needed to pursue a MS in Computer Science:

  • CSC 200 – Computer Science Fundamentals
  • CSC 315 – Object Oriented Programming
  • CSC 325 – Java Programming I
  • CSC 345 Database Foundations

 

Program Competencies

Computer Science – Data Science Concentration

  • Analyze the requirements, scope, and impact of Computer Science concepts effectively and professionally.
  • Apply computer science best practices and current methodologies to create, deliver, and support computer science projects and their importance to practical problems.
  • Evaluate implementation of various models of Machine Learning within a modern organization.
  • Analyze and evaluate scenarios for implementing Deep Learning systems in an organization.
  • Oral Communication - Appraise the needs of the audience and then speak in a clear and succinct manner. Research, construct, and deliver professional presentations using a variety of communication tools and techniques.
  • Written Communication - Write with clarity and precision using correct English grammar: mechanics (punctuation) and usage (sentence structure and vocabulary). Exhibit competence in writing for specific purposes, diverse audiences, and genres. Correctly and ethically present scholarly writings utilizing the selected citation and writing style deemed appropriate for the student's program of study.
  • Disciplined Inquiry - Employ scientific, quantitative and/or qualitative reasoning and other critical thinking strategies to analyze consequences and outcomes and to be able to recommend alternative solutions.
  • Information Literacy - Using information in any format to research, evaluate, and ethically utilize information effectively and with appropriate attribution.
  • Ethics - Demonstrate knowledge and application of prescribed ethical codes and behaviors prompted by the student's chosen profession.

Computer Science – Software Engineering Concentration

  • Analyze the requirements, scope, and impact of Computer Science concepts effectively and professionally.
  • Apply computer science best practices and current methodologies to create, deliver, and support computer science projects and their importance to practical problems.
  • Apply Usability Engineering/Human-Computer Interaction best practices to a scenario.
  • Develop an Information Systems Architecture plan for a modern organization. 
  • Oral Communication - Appraise the needs of the audience and then speak in a clear and succinct manner. Research, construct, and deliver professional presentations using a variety of communication tools and techniques.
  • Written Communication - Write with clarity and precision using correct English grammar: mechanics (punctuation) and usage (sentence structure and vocabulary). Exhibit competence in writing for specific purposes, diverse audiences, and genres. Correctly and ethically present scholarly writings utilizing the selected citation and writing style deemed appropriate for the student's program of study.
  • Disciplined Inquiry - Employ scientific, quantitative and/or qualitative reasoning and other critical thinking strategies to analyze consequences and outcomes and to be able to recommend alternative solutions.
  • Information Literacy - Using information in any format to research, evaluate, and ethically utilize information effectively and with appropriate attribution.
  • Ethics - Demonstrate knowledge and application of prescribed ethical codes and behaviors prompted by the student's chosen profession.


Computer Science Core Course Requirements (15 credits)

All students in the MS Computer Science program will complete the following five core courses (15 credits) and the course requirements (15 credits) in their chosen field of concentration.

CSC 7002 Python Programming

CSC 7003 Algorithms and Advanced Data Structures

CSC 7004 Intro to Data Science

OR

CSC 7005 Principles of Software Engineering

CSC 7006 Ethics in Digital World

CSC 8101 CSC Capstone Project


Data Science Concentration (15 credits)

Students in the MS Computer Science - Data Science concentration will complete the Computer Science core (15 credits) and five courses (15 credits) from the following:

CSC 7020 Theory of Artificial Intelligence

CSC 7021 Cloud-Based Machine Learning

CSC 7022 Deep Learning and Neural Network

Electives List

Select two courses from the following:

CSC 7023 Natural Language Processing (NLP)

CSC 7024 Predictive Analytics: Data Mining

CSC 7025 Data Analytics and Visualization


Software Engineering Concentration (15 credits)

Students in the MS Computer Science - Software Engineering concentration will complete the Computer Science core (15 credits) and 15 credits (four required courses and one elective) from the following:

CSC 7040 Software Engineering Methodologies

CSC 7041 Software Systems Requirements

CSC 7042 Usability Engineering/Human-Computer Interaction

CSC 7043 Information Systems Architecture

 

Electives List

Select one course from the following:

CSC 7044 DevOps

IPM 6050 Agile Project Management

IST 7060 Project and Change Management



This information applies to students who enter this degree program during the 2024-2025 Academic Year. If you entered this degree program before the Fall 2023 semester, please refer to the academic catalog for the year you began your degree program.