Computer Science Major

Learn today’s technology and build tomorrows.

As a Computer Science major, you will demystify codes and algorithms and use them to explore the world. Be a part of revolutionizing technology, including Big Data, Artificial Intelligence (machine learning), computer vision and robots. Grow in your faith while being a part of a Christian community.

Degree Snapshot

Undergraduate - Bachelor's

Degree Types: BA

Concentrations: Cybersecurity

Program Credits: 124

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What will I learn?

Through Houghton’s Computer Science Major, you will:

Develop fundamental programming skills using python and R programming languages. This includes basic data structures, operators, control structures, methods, objects, classes, inheritance, polymorphism, functions, higher order functions, types, and pattern-matching.
Build on classical computer science courses like data structures, computer architecture, operational systems (Linux), and networking and databases.
Explore less conventional areas such as Machine Learning, Deep Learning, Big Data Analytics and Cybersecurity.
Conduct research, tackle a real-world complex issue, or travel in your first year with Houghton’s Science Honors Program.
Gain practical experience in Houghton’s Technology Service Office. Support Houghton's network infrastructure and address computer hardware and software issues.
Publish and present your research at national conferences.

Why study Computer Science at Houghton?

Use the Latest Technology to Build Your Skills

Take a hands-on approach to learning in Houghton's science computer lab. You will develop your technical skills by configuring the components of Single Board Computer (SBC) and debugging syntax and semantic errors from source codes.

Learn about data analytical programming toolkits, construct Convolutional and Deep Learning Neural Networks, and implement embedded image recognition on edge AI devices. Be confident in knowing you'll be ready for the workforce after completing this program.

Research Experience

Use methods from computer technology to address problems in other areas such as sociology and geology. This cross-disciplinary model, allows you to evaluate the model’s performance and analyze results by conducting experiments. Collaborate with Christian faculty who care about your academic, emotional, and spiritual growth and prepare you for a future in your field.

Experiential Learning

Seize the opportunity to conduct summer research at Houghton University’s Shannon Summer Research Institute. You will work closely with faculty mentors on research projects for a period of six to seven weeks before you present your findings. Previous projects include:

data analytics for wind power ramp
Arduino cybersecurity
implementation of embedded image recognition on Jetson Nano platform
implementation of embedded object detection on Jetson Nano platform (CNN & DNN)

Courses & Degree Requirements

Popular Courses

CSCI 226 Computer Architecture

Learn how computers are built and organized. Study the basic language that computers use (machine language) and a simpler way to write computer instructions (assembly language). You'll learn how computers store numbers, how the computer's "brain" (CPU) is organized, and how to write small programs that work together.

CSCI 245 Software Engineering

Learn the foundations of creating professional software. You'll study the step-by-step process of building software, including: planning, designing how it will work, writing the actual code, testing, and keeping the software running smoothly. You'll also learn how software companies create their products in the real world, including how to write important documentation that explains your work.

CSCI 345 Machine Learning

Learn how to teach computers to learn from information. You'll discover how computers can find patterns in data and make decisions on their own. Topics include: how to train computers to sort things into categories, make predictions, and learn from their mistakes. You'll also study different ways computers can learn - including learning with guidance (supervised learning), learning on their own (unsupervised learning), and learning through trial and error (reinforcement learning). The course also covers neural networks, which are computer systems designed to work like the human brain.