Big Data Analytics, M.S.

(Major Code: 05071) (SIMS Code: 112998) (SIMS Code: 112997 - SDSU Global Campus)

In addition to meeting the requirements for classified graduate standing and the basic requirements for the master’s degree as described in Requirements for Master’s Degrees , students must complete 30 units of coursework in an officially approved course of study as outlined below. Students must earn a minimum grade point average of 3.0 in these courses and no less than a C (2.0) in each course. Students may fulfill the culminating experience through Plan A (thesis option) by completing BDA 799A , or through Plan B (non-thesis option) by successfully passing a comprehensive examination.

Students admitted conditionally will be required to take courses in preparation for the Master of Science degree that do not fulfill degree requirements, if conditions warrant.

Advancement to Candidacy

All students must satisfy the general requirements for advancement to candidacy, as described in Requirements for Master’s Degrees .

Required Core Courses

(12 units)

BDA 572 - Python Scripting for Social Science Units: 3 also listed as
LING 572 - Python Scripting for Social Science Units: 3
or
GEOG 582 - GIS Programming with Python Units: 3
BDA 594 - Big Data Science and Analytics Platforms Units: 3 also listed as
GEOG 594 - Big Data Science and Analytics Platforms Units: 3
BDA 602 - Machine Learning Engineering Units: 3
MIS 686 - Enterprise Database Management Units: 3

Electives

(9 units)

Prior approval of electives by the graduate adviser is required for their application towards the degree. Electives may be selected from the following list. Students should be aware that many electives require prerequisites that will not fulfill degree requirements.

ACCTG 621 - Accounting Information Systems Units: 3
ACCTG 673 - Accounting Information Systems (AIS) Development Units: 3
B A 640 - Financial Reporting and Analysis Units: 2
B A 642 - Statistical Analysis Units: 2
BDA 696 - Advanced Special Topics in Big Data Analytics Units: 3
BDA 797 - Research Units: 1-3
BDA 798 - Special Study Units: 1-3
BIOMI 600 - Methods in Bioinformatics, Medical Informatics, and Cheminformatics Units: 3
CS 503 - Scientific Database Techniques Units: 3
CS 514 - Database Theory and Implementation Units: 3
CS 581 - Computational Linguistics Units: 3 also listed as
LING 581 - Computational Linguistics Units: 3
CS 653 - Data Mining and Knowledge Units: 3
ENGL 560 - Literature in the Digital Age Units: 3
ENGL 562 - Digital Methods in Literary Studies Units: 3
GEOG 581 - Data Visualization Units: 3
GEOG 583 - Internet Mapping and Distributed GIServices Units: 3
GEOG 584 - Geographic Information Systems Applications Units: 3
GEOG 593 - GIS for Business Location Decisions Units: 3
GEOG 780 - Seminar in Techniques of Spatial Analysis Units: 3
LING 571 - Computational Corpus Linguistics Units: 3
LING 583 - Statistical Methods in Text Analysis Units: 3
MATH 524 - Linear Algebra Units: 3
MIS 720 - Electronic Business and Big Data Infrastructures Units: 3
MIS 687 - Secure Enterprise Networking and Mobile Technologies Units: 3
MIS 691 - Decision Support Systems Units: 3
MIS 748 - Time Series Analysis for Business Forecasting Units: 3
MIS 649 - Business Analytics Units: 3
SOC 607 - Advanced Quantitative Methods: Core Course Units: 3
SOC 730 - Seminar in Social Institutions Units: 3
STAT 550 - Applied Probability Units: 3
STAT 551A - Probability and Mathematical Statistics Units: 3
STAT 610 - Linear Regression Models Units: 3

Research

(3 units)

BDA 797 - Research Units: 1-3
BDA 798 - Special Study Units: 1-3

Capstone and Culminating Experience

(6 units)

Plan A

BDA 600 - Big Data Analytics Capstone Seminar Units: 3
and
BDA 799A - Thesis or Project Units: 3

Plan B

BDA 600 - Big Data Analytics Capstone Seminar Units: 3
and
Three additional units of elective graduate courses listed above.