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.
Program Outcomes for the Major in Computer Science, Concentration in Big Data Analytics
Graduates of the Big Data Analytics Concentration will be able to (in addition to the Computer Science Major Program Learning Outcomes):
- Apply basic models, methods, programming languages, and tools for data storage, management and processing.
- Apply current data visualization techniques, programming languages, and tools.
- Apply basic statistical data analysis methods, programming languages, and tools.
- Apply cloud and distributed computing techniques, tools, and services to solve real-word Big Data problems.
- Evaluate, select, and apply data mining models, methods, and tools for real-word problems.
- Evaluate, select, and apply tools and technologies to analyze and solve Big Data problems.
A laptop computer running Windows, macOS, or Linux is required for courses in the Computer Science program. 16GB of memory is suggested. A Chromebook will not work.
Requirements for the Concentration in Big Data Analytics
| Code | Title | Credits |
|---|---|---|
| Core Courses | (38 credits) | |
| CS-101 | Basics of Computer Science | 3 |
| CS-140 | Introduction to Programming | 4 |
| CS-155 | Computer Networking and Security | 3 |
| CS-225 | Discrete Structures I | 3 |
| CS-242 | Data Structures | 3 |
| CS-248 | Algorithm Analysis | 3 |
| CS-254 | Computer Organization and Architecture | 4 |
| CS-282 | Unix Systems Programming | 3 |
| CS-286 | Database Design and Applications | 3 |
| CS-295 | Discrete Structures II | 3 |
| CS-348 | Software Process Management | 3 |
| CS-373 | Operating Systems | 3 |
| Elective Courses | (3 credits) | |
| Credits in Computer Science courses at the 300 level or above 1 | 3 | |
| Ancillary Requirements 2 | (31 credits) | |
| CM-110 | Public Speaking | 3 |
| EN-252 | Technical Writing | 3 |
| UR-230 | Technology, Public Policy and Urban Society | 3 |
| or PH-134 | Computing Ethics | |
| MA-150 | Statistics I 3 | 3 |
| or MA-302 | Probability and Statistics | |
| MA-200 | Calculus I | 4 |
| 2 lab science courses | 8 | |
| 2 approved math or science course chosen from a department-approved list of courses 4 | 7 | |
| Requirements for the Concentration in Big Data Analytics | (9 credits) | |
| CS-383 | Cloud, Parallel an Distributed Computing | 3 |
| CS-453 | Data Mining | 3 |
| CS-483 | Big Data Analytics Capstone | 3 |
| Total Credits | 81 | |
- 1
Up to 3 credits of Internship (CS-498) and up to 3 credits of Independent Study (CS-499) may be used to satisfy the major elective requirements.
- 2
31 credits (may apply to LASC requirements). These ancillary courses cannot be taken on a pass/fail basis
- 3
Students planning a Mathematics minor or a Computer Science/Mathematics double major should take MA-302.
- 4
Students planning a Mathematics minor or a Computer Science/Mathematics double major should take math courses required for the Mathematics minor/major.
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.
| Year One | ||
|---|---|---|
| Semester One | Credits | |
| CS-101 | Basics of Computer Science | 3 |
| EN-101 | College Writing I | 3 |
| MA-190 | Pre-calculus (or Math/Science Course) 1,2 | 4 |
| LASC | First-Year Seminar (FYS) | 3 |
| LASC | LASC Elective (CON) 3 | 3 |
| Credits | 16 | |
| 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 |
| Credits | 14 | |
| 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 |
| UR-230 or PH-134 | Technology, Public Policy and Urban Society or Computing Ethics | 3 |
| Credits | 15 | |
| Semester Four | ||
| CS-282 | Unix Systems Programming | 3 |
| CS-295 | Discrete Structures II | 3 |
| CM-110 | Public Speaking | 3 |
| LASC | LASC Elective (GP) 3 | 3 |
| LASC | LASC Elective (CA) | 3 |
| Credits | 15 | |
| Year Three | ||
| Semester Five | ||
| CS-248 | Algorithm Analysis | 3 |
| CS-254 | Computer Organization and Architecture | 4 |
| CS-348 | Software Process Management | 3 |
| MA-150 or MA-302 | Statistics I 4 or Probability and Statistics | 3 |
| LASC | Lab Science (DAC) | 3 |
| Credits | 16 | |
| Semester Six | ||
| CS-373 | Operating Systems | 3 |
| CS-383 | Cloud, Parallel an Distributed Computing | 3 |
| LASC | Math or Science course 2 | 3-4 |
| LASC | Lab Science (NSP) | 4 |
| LASC | LASC Elective (USW) 3 | 3 |
| Credits | 16-17 | |
| Year Four | ||
| Semester Seven | ||
| CS-453 | Data Mining | 3 |
| LASC | LASC Elective (NSP) 3 | 4 |
| SELECT | General Elective | 3 |
| SELECT | General Elective | 3 |
| Credits | 13 | |
| Semester Eight | ||
| CS-483 | Big Data Analytics Capstone | 3 |
| LASC | LASC Elective (ICW) 3 | 3 |
| SELECT | 300+ Level Elective in Major | 3 |
| SELECT | General Elective | 3 |
| SELECT | General Elective | 3 |
| Credits | 15 | |
| Total Credits | 120-121 | |
- 1
If the students math placement score requires her/him to take MA-190, it should be taken this semester, so that MA-200 can be taken in the Spring semester. EN-101 & EN-102 satisfy LASC writing requirements.
- 2
All Math and Science courses must be selected from a list of department approved courses.
- 3
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
- 4
Students planning a Mathematics minor or a Computer Science/Mathematics double major should take MA-302.
Note:
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 academic advisor to review their courses for the upcoming semester. A minimum of 120 credits is required for graduation. First-year and transfer students with 45 or fewer credits at the time of admission shall complete two academic programs (a major/major or major/minor) to qualify for graduation. For more information, please view the MajorPlus section of this catalog.