In the Master of Science in Computer Science program, you will develop the skills and knowledge necessary to analyze, synthesize, and evaluate solutions for real-world problems using techniques from computer science. By staying updated on current practices in systems, networks, tools, algorithms, and advanced topics, you will demonstrate expertise in the field.
Learning Outcomes
- Self-Sufficient Learning: Demonstrate the ability to independently assess your knowledge and skills in computer science by formulating relevant questions and seeking additional resources as needed.
- Project Management: Create effective timelines and identify necessary resources to meet the demands of assigned projects, ensuring timely and successful completion.
- Self-Assessment and Reflection: Accurately assess your own work, reflect on your approaches, and adjust strategies to achieve improved outcomes in computational tasks and projects.
- Ethical Knowledge and Practice: Understand and apply ethical considerations in computing, consistently acting in an ethical and moral manner in academic and professional contexts.
- Intellectual Property and Professional Responsibility: Honor copyrights and patents, give proper credit for intellectual property, respect confidentiality and privacy rights, and access authorized computing and communication resources.
- Professional Competence: Maintain professional competence by continuously updating skills and knowledge, documenting risks or faults in system designs, and taking full responsibility for your work.
- Career Preparedness: Demonstrate readiness for employment in computer science-related fields, equipped with the expertise and practical experience needed for success in roles such as software development, data analysis, network administration, and more.
- Comprehensive Curriculum Mastery: Show mastery of the comprehensive curriculum through successful application of theoretical knowledge and practical skills in real-world scenarios.
- Industry-Relevant Skills: Develop industry-relevant skills that enable you to thrive in various computer science roles, adapting to evolving technological landscapes and industry demands.
- Lifelong Learning: Foster a commitment to lifelong learning, staying current with advancements in computer science and continuously seeking opportunities for professional growth.
Program Requirements - 30 credits
Core Courses (12 credits)
One core course must be taken from each of the following four core areas:
- COSC 510 or 511 Advanced Operating Systems and Computer Architecture
- COSC 512 or 513 Artificial Intelligence and Data Management Systems
- COSC 514 or 515 Networks and Security
- COSC 516 or 517 Algorithms and Models of Computation
Advanced Courses (3 credits)
Advanced courses build on the core courses and provide more depth in the core areas.
- COSC 521 Automated Theorem Proving
- COSC 522 Data Compression
- COSC 523 Machine Learning
- COSC 524 Natural Language Processing
- COSC 525 String Processing
- COSC 560 Algorithms/Graph Theory
Internship (0-3 credits)
A requirement of the program is to gain useful, real-world experience applying the
tools and concepts acquired in the course of study.
If you have no prior, relevant work experience, you will be required to complete an
internship or employment experience, typically during the summer term.
If you have prior, relevant work experience, you may satisfy the internship requirement
by submitting suitable materials. These materials include an academic reflection that
addresses the skills, knowledge, techniques and design principles related to computer
science acquired in your work, along with a portfolio of related work projects, including
design documents, programs and documentation as appropriate, which demonstrate a mastery
of these areas.
All Duquesne students have access to Handshake through the Center for Career Development as one of the tools in finding internships.
Electives (12-15 credits)
The computer science electives must be at the 500 level or above. If a core area has
been satisfied, any additional course taken in that core area may be counted as an
elective.
You may take up to six credits of 500-level courses outside the program with departmental
approval. These credits may be earned at Duquesne or at other approved institutions,
including at Carnegie Mellon or the University of Pittsburgh through cross-registration.
- COSC 530 Web-based Systems
- COSC 531 Parallel and Distributed Computing
- COSC 532 Data Visualization
- COSC 533 Compilers
- COSC 535 Theory of Programming Languages
- CPMA 551 Digital Image Processing
- CPMA 565 Numerical Methods
- CPMA 566 Operations Research
- CPMA 573 Statistical Computing