Analytics and Data Science Major: Data Science Option (B.S.)

https://ceps.unh.edu/computer-science/program/bs/analytics-data-science-major-data-science-option

The option in Data Science is intended for students interested in pursuing advanced degrees and conducting original research in data science. The option in data science places its emphasis on a rigorous introduction to the theoretical mathematical and computational underpinnings of modern data science.

Program Objectives

This program has been designed to prepare students for professional careers working with data, with an emphasis on the extraction of meaning from data. The program is not targeted to any one industry; rather, it provides a flexible, practical skillset that can be applied widely. This skillset includes elements of computer science, applied mathematics and statistics, communication skills, and business savvy. Graduates of the bachelor of science in analytics and data science program are expected to have:

  • An understanding of the role of data in guiding decision-making in industry
  • An understanding of how data is generated, stored, and accessed
  • An understanding of data security
  • An understanding of the ethical use of data
  • An understanding of structured vs. unstructured data
  • An understanding of the methods, statistical and other, used to derive actionable information from data
  • Experience with multiple programming languages
  • Experience with multiple statistical and data analysis software programs
  • The ability to communicate detailed, technical information to a variety of audiences clearly and concisely, without the use of jargon
  • The ability to work effectively, both as an individual or as a member of a team
  • The ability to successfully lead a team
  • The ability to adapt to a dynamic, rapidly changing work environment
  • Completed projects and other work experiences on a larger scale than is typical in a bachelor's degree program.

During the course of the program, students will demonstrate their acquisition of these skills by successfully completing their program coursework, their internship experience, and their capstone project.

Successful completion of the program entails earning at least 128 credits, meeting the requirements of the University's Discovery program, completing all of the 20 required courses in the major as listed below, including the capstone course, the internship preparedness course, and a three-credit internship. In all major courses, the minimum allowable grade is a C-. The minimum overall GPA for graduation is 2.0. Transfer students may transfer up to a maximum of 32 credits to satisfy major requirements (not counting those courses used to satisfy Discovery requirements).

Program Requirements

Mathematics
MATH 425Calculus I4
MATH 426Calculus II4
MATH 528Multidimensional Calculus4
MATH 531Mathematical Proof4
MATH 539Introduction to Statistical Analysis4
or MATH 644 Statistics for Engineers and Scientists
or COMP 570 Statistics in Computing and Engineering
MATH 645Linear Algebra for Applications4
MATH 755Probability with Applications4
MATH 756Principles of Statistical Inference4
Computer Science
CS 400Introduction to Computing1
CS 414
CS 417
From Problems to Algorithms to Programs
and From Programs to Computer Science
8
or CS 415
CS 416
Introduction to Computer Science I
and Introduction to Computer Science II
or COMP 424
COMP 525
Applied Computing 1: Foundations of Programming
and Data Structures Fundamentals
or COMP 425
COMP 525
Introduction to Programming
and Data Structures Fundamentals
CS 457Introduction to Data Science and Analytics4
or DATA 557 Introduction to Data Science and Analytics
CS 515Data Structures and Introduction to Algorithms4
or COMP 625 Data Structures and Algorithms
CS 659Introduction to the Theory of Computation4
CS 750
MATH 738
Machine Learning
and Data Mining and Predictive Analytics
8
or DATA 674
DATA 675
Predictive and Prescriptive Analytics I
and Predictive and Prescriptive Analytics II
or DATA 674
CS 750
Predictive and Prescriptive Analytics I
and Machine Learning
CS 758Algorithms4
CS 775Database Systems4
English
ENGL 502Professional and Technical Writing4
Analytics Course
DATA 790Capstone Project 14
or CS 791
CS 792
Senior Project I
and Senior Project II
or CS 799 Thesis
Select three electives 212
Total Credits89

For additional information about the Analytics and Data Science: Analytics Option, contact Wheeler Ruml, program co-director (Durham campus), at wheeler.ruml@unh.edu or Jeremiah Johnson, program co-director (Manchester campus), at (603) 641-4127 or jeremiah.johnson@unh.edu.

  • Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
  • Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
  • Communicate effectively in a variety of professional contexts.
  • Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
  • Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
  • Apply theory, techniques, and tools throughout the data analysis lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.