Data Science

Reach new heights with a degree in data science from Northern Vermont University

Data is at the center of many positions in today's modern job market, and the ability to interpret data is a highly sought-after skill by most employers. Northern Vermont University's new degree in data science will prepare you to make data-based decisions, inferences, and predictions using industry-standard programs and software — giving you the skills to make your impact in a career beyond NVU.

Hands-On Skill Building

As a data science major, your first few semesters will focus on mathematics and computer science. You will become proficient in a computer programming language and apply foundational mathematics and computer science knowledge to real-world problems. Once proficient in technical and analytical skills, you will select elective courses in business or behavioral sciences to apply what you have learned and gain hands-on experience analyzing data. 

To expand on your experiential learning opportunities, you will enroll in a capstone project course in your third or fourth year of the program. This includes an independent project based on your individual interests in data science and will allow you to apply the skills you have learned toward a subject of your choice.   

Student Learning Outcomes 

  • Graduate as proficient consumers, creators, and communicators of data for both technical and general audiences.
  • Proficiency in a computer programming launguage
  • Apply foundational mathematics and computer science to problems in data science
  • Understand how to acquire, store, and manage data in a variety of formats and scale.

A core assessment examination is administered near the end of the second year to assess that students are developing the skills described in the above learning objectives.

Degree Requirements

Core Courses (45 credits)
Calculus I (4 credits)
Statistics (3 credits)
Linear Algebra (3 credits)
Business Software and Spreadsheets (3 credits)
Problem Solving with Computers (3 credits)
Java Programming (3 credits)
Advanced Object-Oriented Programming (3 credits)
Data Structures and Algorithms (3 credits)
Data Systems (3 credits)
The Visual Display of Quantitative Information (3 credits)
Statistical Computing in R (3 credits)
Data Science I (4 credits)
Data Science II (4 credits)
Senior Project in Mathematics and Computer Science (3 credits)
 
Electives (6 - 8 credits)
Project Management (3 credits)
Financial Accounting (4 credits)
Principles of Marketing (3 credits)
Market Research (3 credits)
Research Design and Analysis (3 credits)
Science, Research Methods and Ethics (3 credits)
Calculus 2 OR Calculus 3 (4 credits)
Probability Theory with Statistics (3 credits)