Computer Science Major, Concentration in Big Data Analytics

Data is being generated at high speed, in large volumes, and by a variety of systems around the world. In such a data-driven and information-centric world, the ability to analyze information and make informed decisions is crucial to every field including business, medicine, the sciences, entertainment, and government. This concentration provides students with the skills, techniques, and knowledge needed to pursue a career in this field.

Requirements for the Concentration in Big Data Analytics

Core Courses(38 credits)
CS-101Basics of Computer Science3
CS-140Introduction to Programming4
CS-155Computer Networking and Security3
CS-225Discrete Structures I3
CS-242Data Structures3
CS-248Algorithm Analysis3
CS-254Computer Organization and Architecture4
CS-282Unix Systems Programming3
CS-286Database Design and Applications3
CS-295Discrete Structures II3
CS-348Software Process Management3
CS-373Operating Systems3
Elective Courses(3 credits)
Credits in Computer Science courses at the 300 level or above 13
Ancillary Requirements 2(31 credits)
CM-110Public Speaking3
EN-252Technical Writing3
UR-230Technology, Public Policy and Urban Society3
or PH-134 Computing Ethics
MA-150Statistics I 33
or MA-302 Probability and Statistics
MA-200Calculus I4
2 lab science courses8
2 approved math or science course chosen from a department-approved list of courses 47
Requirements for the Concentration in Big Data Analytics(9 credits)
CS-383Cloud, Parallel an Distributed Computing3
CS-453Data Mining3
CS-483Big Data Analytics Capstone3
Total Credits81

Department of Computer Science: Big Data Analytics Concentration Sample Timeline for Completion of Degree

This four-year plan assumes a Math Placement score of at least 6.

Plan of Study Grid
Year One
Semester OneCredits
CS-101 Basics of Computer Science 3
EN-101 College Writing I 3
MA-190 Pre-calculus (or Math/Science Course) 1,2 4
LASCFirst-Year Seminar (FYS) 3
LASCLASC Elective (CON) 3 3
Semester Two
CS-140 Introduction to Programming 4
CS-155 Computer Networking and Security 3
EN-102 College Writing II 3
MA-200 Calculus I 4
Year Two
Semester Three
CS-225 Discrete Structures I 3
CS-242 Data Structures 3
CS-286 Database Design and Applications 3
EN-252 Technical Writing 3
Technology, Public Policy and Urban Society
or Computing Ethics
Semester Four
CS-282 Unix Systems Programming 3
CS-295 Discrete Structures II 3
CM-110 Public Speaking 3
LASCLASC Elective (GP) 3 3
LASCLASC Elective (CA) 3
Year Three
Semester Five
CS-248 Algorithm Analysis 3
CS-254 Computer Organization and Architecture 4
CS-348 Software Process Management 3
Statistics I 4
or Probability and Statistics
LASCLab Science (DAC) 3
Semester Six
CS-373 Operating Systems 3
CS-383 Cloud, Parallel an Distributed Computing 3
LASCMath or Science course 2 3-4
LASCLab Science (NSP) 4
LASCLASC Elective (USW) 3 3
Year Four
Semester Seven
CS-453 Data Mining 3
LASCLASC Elective (NSP) 3 4
SELECTGeneral Elective 3
SELECTGeneral Elective 3
Semester Eight
CS-483 Big Data Analytics Capstone 3
LASCLASC Elective (ICW) 3 3
SELECT300+ Level Elective in Major 3
SELECTGeneral Elective 3
SELECTGeneral Elective 3
 Total Credits120-121


The sequence of LASC courses marked with 3 is a suggestion but serves as a reminder that LASC designated courses must be taken to satisfy the LASC requirements.

Once LASC requirements are satisfied, students may select general requirements. Please refer to the University Catalog for specific curriculum details regarding major and LASC requirements.



Students are required to meet with their department advisor to review their upcoming semester academic choices. A minimum of 120 credits is required for graduation.