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Computer Science Degree

Program Offerings

• Bachelor of science in Computer Science
• Bachelor of science in Applied and Computational Mathematics
• Master of science degree in Computational Sciences and Robotics
• Accelerated master’s in Computational Sciences and Robotics (earn your bachelor’s and master’s in as little as five years)
• Minors: Computational Statistics, Computer Science, Mathematics, Robotics.
• Certificates: Computational Statistics, Computer Science, Mathematics, Robotics, HBX CORe Credential of Readiness for Business and Technology Innovation

What is Computer Science?

Computer science is the study of computers and computational systems. Essentially, the field of computer science deals with data and how that data can be manipulated to solve problems.

Computers are a part of nearly every aspect of modern life, which is why computer science is such an important field of study. The profession is projected to grow 19 percent from 2016 to 2026 as the demand for new and better technology grows. Mines' project-driven curriculum challenges students to take an app from idea to market in a semester or start a business through a new entrepreneurship course with a seat at start-up boot camp for the winning pitch.

What does a computer scientist do?

Computer scientists invent and design new approaches to computing technology and find new, innovative applications for existing technology. They program software, create mobile apps, develop websites and secure information. Computer scientists teach computers what to do using the computer’s language or code. Computer scientists work in virtually every sector of the economy from artificial intelligence and virtual reality to health sciences and finance.

Duties of a computer scientist might include:
• Explore fundamental issues in computing and create theories and models to manage those issues
• Assist scientists and engineers in solving complex computing problems
• Invent new computing languages, tools and methods to improve interactions between computers and humans
• Develop and improve software systems
• Design experiments to test software systems
• Analyze experiment results

First-Year Courses

Survey of computer science
Computer science I
Calculus
Programming & Techniques
Physics
Composition

Course Curriculum

Link to Catalog

Internships and Co-ops

Through cooperative education (co-ops) and internships, SD Mines students have many opportunities to apply their education to "real world" work experiences. Students are employed by industry and government agencies in positions related to mathematics and computer science. Computer science majors who take advantage of internships and co-ops earn an average $18.45/hour. Computer science majors have interned at such companies as:
• Google
• Amazon
• Roger Opp Linux Lab
• Mobile Computing Lab
• L-3 Communications Embedded Systems
• Robotics Lab

Career Outlook

The average starting salary for a SD Mines computer science graduate is $68,126.

Careers

Careers in computer science might include:
• Software developer
• Database administrator
• Software engineer
• Database design and management
• Parallel computing
• Programming, virtual reality
• Robotics
• Mob web development
• Information security analysts
• Computer programmer
• Information assurance and cryptography

Employers

SD Mines computer science graduates are employed by such companies as:
Amazon
Microsoft
Innovative Systems
Google
Raytheon Missile Systems
Black Hills Corp
EchoStar
Los Alamos National Lab
Golden West
NISC
L-3 Communications
Schwan Food Co.

Computer Science Research

Some research focus areas include:
• numerical linear algebra and multilinear algebra
• non-parametric statistics, computational statistics, time series forecasting, massive data streams
• combinatorial matrix theory, graph theory, and modeling
• math biology, math ecology, applied math and Bayesian statistics
• Scientific Visualization, High Performance Computing, (HPCC), and Problem Solving Environments
• finite geometry, non-associative algebras
• parameter estimation and decision theory, computationally intensive statistical methods, statistics pedagogy
• algorithms and software for multicore architectures, topology aware MPI communications and scalable checkpointing techniques.
• mobile robotics path planning, localization and mapping, and computer vision; evolutionary algorithms, particle and swarm methods, and biologically motivated algorithms
• numerical linear algebra, mathematical modeling, and image processing, and program assessment

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