Bachelor of Science in Data Analytics

The Bachelor of Science in Data Analytics program coursework explores the mathematical skills and programming language needed to analyze and interpret data. The capstone course culminates the program and provides an opportunity for students to apply the skills they learned throughout the program. Students must complete 120-semester credits (including transfer credits) to earn their bachelor's degree.

The program consists of the following curriculum areas:

• Core courses give students in-depth knowledge of data science mathematical foundations and technology-enhanced techniques.
• Tailor your data analytics degree with Norwich’s range of course electives to complete the required 120 total credit.
• Demonstrate knowledge learned in data analytics in the Capstone project.
   

Core Curriculum and Capstone (50 credits)

Students complete the following coursework. The program's coursework culminates with the capstone.

• Pre-Calculus

  MA107 4 credit hours

  A course on topics in precalculus mathematics involving algebra and trigonometry designed to prepare students to progress into introductory calculus. It is a rapid development of elementary topics in algebra to linear, quadratic, logarithmic, and exponential functions, followed by an analytical treatment of trigonometry. 

• Applied Calculus

  MA108 4 credit hours

  A course on topics in analytical geometry progressing to differential and integral calculus. Presentation of a wide variety of practical application to technology, business, and science. Prerequisite: MA 107 or equivalent as determined by departmental placement testing.

• Discrete Mathematics

  MA306 3 credit hours

  A course in logic, sets, techniques of proof, relations and functions, directed and undirected graphs, algebraic systems, Boolean algebra, and emphasis on applications in various areas of computer science. Prerequisite: MA 108 or MA 121 and knowledge of computer programming.

• Linear Algebra

  MA310 3 credit hours

  A theoretical course on such topics as matrices, determinants, linear equations, vector spaces, bases and dimensions, linear transformations, eigenvalues, and eigenvectors. 

• Advanced Statistical Methods

  MA332 3 credit hours

  This course provides a firm foundation for the employment of statistical methodology in data science. Examples drawn from data science will be used throughout. The course will cover descriptive statistics, probability, continuous and discrete statistical distributions, regression, multiple regression, maximum likelihood estimate, logistic regression and the likelihood ratio test. Pre-reqs: MA306.

• Relational Database Management w/ SQL

  CYBR230 3 credit hours

  This course covers the fundamental concepts of relational databases and the scripted Structure Query Language (SQL) language used to manage them. Students will learn how to design functional relational databases that conform to industry standards. Prerequisite: None

• Programming in Julia *

  CS145 3 credit hours

  * This course is currently under development. 

• Programming in Python *

  CS146 3 credit hours

  * This course is currently under development. 

• Introduction to Data & Business Analytics

  DTAN301 3 credit hours

  This course introduces students to the discipline and techniques of data analytics and their application in business. Students develop a theoretical and practical approach to business problem solving utilizing end-to-end business analytics processes as well as IT programming constructs to meet the business goals of an organization. Topics introduced include data and web mining, regression, classification, recommendation systems, text mining, data visualization, and neural networks implementation using a hands-on approach. Pre-reqs: none.  

• Algorithm Design and Implementation *

  DTAN310 3 credit hours

  * This course is currently under development. 

• Introduction to Machine Learning & Artificial Intelligence *

  DTAN320 3 credit hours

  An introduction to the basic principles, techniques, and applications of Machine Learning and Artificial Intelligence. Coverage includes exploratory data analysis, data engineering and data preparation, model selection, various regression models and model evaluation. Students will experience programming in both R Studio and Python. (3 credits) Prerequisites: None

• Introduction to Network Science

  DTAN330 3 credit hours

  In this course, students learn how to analyze social media feeds, news, and full-text publications to derive insightful findings. They explore the foundations of network constructions, network types, communities, and the common network phenomena and algorithms. This is a hands-on course requiring proficiency in the programming language Python. Pre-reqs: A course on programming in Python or an equivalent language.

• Data Visualization

  DTAN344 3 credit hours

  Data visualization is the art and science of turning data into readable graphics for the purpose of storytelling and enabling stakeholder to make data driven decisions. Students learn how to detect and articulate the stories behind data sets and communicate data findings in visual, oral, and written contexts for various audiences. Students become familiar with associated tools for data visualization.  Pre-req: NONE

• CLIPS: Programming for Expert Systems *

  DTAN410 3 credit hours

  * This course is currently under development. 

• Data Analytics Capstone

  DTAN400 6 credit hours

  Students research and apply skills learned in an area of data analytics.

Norwich University, in compliance with Title IV of the Civil Rights Act of 1964, Title IX of the Education Amendment of 1972, and Section 504 of the Rehabilitation Act of 1973, does not discriminate on the basis of race, religion, color, national origin, age, sex, or physical handicap in any of its policies, practices, or procedures.

Meet some graduates from our online bachelor's programs.

From the very beginning of submitting my application to graduation day, the one-on-one interaction with the faculty and staff made me feel a part of the Norwich family.

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Steve Gonzalez
Class of 2016

Bachelor of Science in Strategic Studies and Defense Analysis

I have always dreamed about graduating from Norwich University. Going to college was always on my bucket list and this was my motivation.

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Kelley Lawrence
Class of 2016

Bachelor of Science in Criminal Justice

One of the key things to me for having a Norwich education is the name that comes with it; there’s pride and tradition that comes with having a Norwich University diploma. It’s finishing what I started here many years ago and I wanted something I can be proud to hang in my office.

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Julie Scribner
Class of 2015

Bachelor of Science in Criminal Justice

Norwich has developed online programs to maximize your career potential. Get to know a few graduates -- with busy schedules -- and how they made their education fit into their lifestyles.