M.S. in Computer Engineering
Tarleton State University
Key Information
Campus location
Online
Languages
English
Study format
Distance Learning
Duration
18 months
Pace
Full time
Tuition fees
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Application deadline
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Earliest start date
Sep 2024
* tuition depends on if student decides to take 2 or 1 class every 8 weeks
Scholarships
Explore scholarship opportunities to help fund your studies
Introduction
The M.S. in Computer Engineering program brings students to the leading edge of computer engineering by solving real-life problems which then contributes to the advancement of local communities and of society as a whole. This program is designed to prepare students for career advancement, or for further studies at the doctoral level. It has two options, thesis and professional (non-thesis). It is a research-based program of study, requiring students to complete independent research that culminates in several projects, and, in one of the options, with a thesis project.
Unique to our program is the focus on optimization and stochastic models, taught by experienced faculty who have extensive expertise in convex optimization for design of VSLI circuits, application of semi-Markov models for optimization of wireless networks, and queueing theory for tele-traffic analysis.
Designed With You in Mind
Either option includes a rigorous curriculum and allows students to concentrate their program in the following specialized areas:
- Computer Architecture and Distributed Computing
- Advanced Computer Networks (including Cybersecurity)
- VLSI Circuit Design
- Robotics, Artificial Intelligence, and Machine Learning (including Computer Vision)
Students gain marketable skills that propel them to being leaders in computer-related industries:
- Ability to identify and solve complex technology problems in robotics, aerospace, business, medicine, military and other essential areas.
- Soft skills in complex problem-solving, communication and creative thinking. A computer engineer must communicate with end-users, managers and vendors to determine computing goals and system requirements, but also with other scientists to solve the complex computing problems that arise.
- Ability to apply and adapt theoretical principles to develop new computer software and/or hardware.
- Computer-related math skills, e.g., linear algebra, calculus, statistics, discrete mathematics, and optimization.
- Fluency in the main current programming languages, such as C/C++; must continue learning new languages as they emerge.
- Technical writing skills to document and publish their findings and designs.
- Ability to teach engineering and computer science across all levels of academia.
- Complex systems engineering
- Logic (circuit) design
Accreditation
Southern Association of Colleges and Schools Commission on Colleges (SACSCOC).
Program Outcome
Students in our program will:
- Be able to understand logic (circuit) design.
- Be able to identify and solve complex technology problems in robotics, aerospace, business, medicine, military, and other essential areas.
- Be able to apply and adapt theoretical principles to develop new computer software and/or hardware.
- Be able to apply Computer-related math skills, e.g., linear algebra, calculus, statistics, discrete mathematics, and optimization in real-world problems.
Career Opportunities
The job market for people with a Master’s degree in Computer Engineering extends over many of the occupations defined by the BLS. Based on our faculty’s experience, the following categories and occupations have the best potential for applicants with this degree:
- Computer and Information Research Scientists
- Computer and Information Analysts
- Computer System Analysts
- Information Security Analysts
- Software Developers and Programmers
- Computer Programmers
Curriculum
Coursework Highlights
Class | Number | Class Name |
CPEN | 5341 | Advanced Algorithms |
CPEN | 5343 | Advanced Computer Architecture |
CPEN | 5351 | Introduction to Convex Optimization |
CPEN | 5355 | VLSI Architectures |
CPEN | 5378 | Advanced Computer Networks |
COSC | 5360 | Artificial Intelligence |
CPEN | 5342 | Parallel Computing and Algorithms |
Research Opportunities
Both students and faculty members continually do research in applied probability and artificial intelligence. Students are encouraged to pursue research alongside faculty members, which will enhance their learning experience, as well as enable them to engage in networking, amplify their resume, and earn some extra money along the way. Past research endeavors have targeted areas such as:
- Game development
- Graphics
- Autonomous robots