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

Analytics and Data Science focuses on the extraction of meaning from data through the application of computer science, mathematics and business domain knowledge. Within a few years of obtaining a bachelor's degree in Analytics and Data Science, our alumni will have:

  1. Engaged in successful career areas of analytics and data science and will already have, or be pursuing, advanced degrees in Analytics, Data Science, Computer Science, Mathematics or related fields
  2. Applied the full range of core Data Science concepts and techniques to fill the analytics needs of an organization
  3. Communicated effectively with diverse stakeholders as well as functioned appropriately in a team environment
  4. Navigated the complex interconnections between data, computing technology, and the goals and constraints of the organization served
  5. Understood the pervasive and changing role of data in global society, and participated responsibly as both an Analytics and Data Science professional and citizen

For additional information about the Analytics and Data Science: Analytics Option, contact Matt Magnusson, program co-director (Durham campus), or Jeremiah Johnson, program co-director (Manchester campus), at (603) 641-4127.

Degree Requirements

Minimum Credit Requirement: 128 credits
Minimum Residency Requirement: 32 credits must be taken at UNH
Minimum GPA: 2.0 required for conferral*
Core Curriculum Required: Discovery & Writing Program Requirements
Foreign Language Requirement: No

All Major, Option and Elective Requirements as indicated.
*Major GPA requirements as indicated.

Major Requirements

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).

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 Computing2
CS 415Introduction to Computer Science I4
or CS 410P Introduction to Scientific Programming/Python
or COMP 424 Applied Computing 1: Foundations of Programming
CS 416Introduction to Computer Science II4
or COMP 525 Data Structures Fundamentals
CS 420Foundations of Programming for Digital Systems4
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 Capstone:
DATA #790Capstone Project 14
or CS 791
& CS 792		 Senior Project I
and Senior Project II
or CS 799 Thesis
Select Approved Minor 220
Total Credits102
1

Fulfills capstone requirement

2

Minor must be approved by an academic advisor and must be in a discipline to which Analytics & Data Science can be applied (i.e. Economics or Applied Mathematics).

  • 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.