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Computer Science Degree

Program Offerings

• Degree: Bachelor of Science (BS) in Computer Science.
• Degree: Master of Science (MS) in Computer Science and Engineering (traditional or accelerated).
• Degree: Doctor of Philosophy (PhD) in Data Science and Engineering.
• Specializations: Artificial Intelligence (Al) and Machine Learning (ML), Cybersecurity, Visual and Interactive Computing.
• Minors: Robotics, Mathematics.

Computer Science (BS) is accredited by the Computing Accreditation Commission of ABET http://www.abet.org.

What is Computer Science?

Computer science is foundational in applying and studying interactions between humans and computers. Computer science and computer scientists study computers, computing, the software and hardware in a computer, and their applications in our modern society.

Software is arguably one of the most rapidly-changing fields in science and engineering. It exists everywhere in our daily lives, and the data it creates exists all around us.

What does a computer scientist do?

Students studying computer science at South Dakota Mines gain expertise and experience in all phases of software development, including design, architecture, implementation, testing, and deployment. Computer science students at Mines will become effective in communicating and operating in a team environment and will gain exposure to many different software languages, technologies, and platforms. The hands-on and immersive experience is at the heart of the computer science program at South Dakota Mines.

Students majoring in computer science at Mines gain exposure to robotics, machine learning, artificial intelligence, intelligent systems, cybersecurity, virtual reality, data science, and application development.

Students prepare for these roles: software developer, software engineer, data scientist, data analyst, software tester, security analyst, and application developer.

Courses for this Degree

• Data Structures & Algorithms
• Test-Driven Software Development
• Introduction to Digital Systems
• Finite Structures
• Operating Systems and Virtual Machines
• Programming Languages
• Graphical User Interface Programming

Course Curriculum

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Internships and Co-ops

At South Dakota Mines, 70% of computer science students land internships, earning an average salary of $21.20 per hour. Students in the computer science program work for these companies, to name a few:

● Amazon
● CNH and Raven Industries
● Garmin
● Google
● Innovative Systems
● Interstates
● L3Harris
● Microsoft
● NASA
● Lockheed Martin
● Omnitech
● SpaceX

Career Outlook

South Dakota Mines computer science graduates typically earn an average starting salary of $78,622. The 2021-2022 job placement rate was 98%.

Careers

Opportunities or Roles

● Artificial Intelligence (Al)
● Augmented Reality (AR)
● Computer Scientist
● Data Scientist or Data Engineer
● Database Administrator
● High-Performance Computing (HPC)
● Information Security Analyst
● Information Assurance and Cryptography
● Machine Learning (ML)
● Mobile Application Development
● Robotics and Automation
● Software Developer
● Software Engineer
● Web Application Development
● Virtual Reality (VR)

Employers

Potential Employers

● Black Hills Energy
● CNH and Raven Industries
● Echostar
● Epic Systems
● Garmin
● Google
● Golden West Telecommunications
● Innovative Systems
● L3Harris
● Meta
● Microsoft
● Omnitech, Inc.
● Property Meld
● Raytheon Technologies
● US Department of Justice

Computer Science Research

Undergraduates studying computer science at South Dakota Mines, in addition to graduate students, have opportunities to engage and get involved in research. These are the primary research focus areas of the faculty.

● Mobile robotics path planning, localization and mapping, computer vision; evolutionary algorithms, particle and swarm methods, and biologically motivated algorithms.

● Scientific visualization, high-performance computing (HPC), problem-solving environments, algorithms and software for multicore architectures, topology-aware MPI communications, and scalable checkpointing techniques.

● Probabilistic artificial intelligence, statistical machine learning, neural networks, stochastic control theory, robotics, intelligent control, and computer vision.

● Cybersickness (visually induced motion sickness from a virtual environment), 3D systems, virtual reality (VR), user interfaces, and analysis of algorithms.

● Computer vision, machine learning, data analytics, dynamic systems and control, multilinear subspace learning, and graph-based forecasting.

● Autonomous cyber-physical system security (attack detection and recovery), web security, mobile operating system security, application security, network security, privacy and anonymity, and machine learning security (adversarial attacks).

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