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MS in Big Data Analytics

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PROGRAM OVERVIEW

 

COURSE DELIVERY METHOD DURATION TOTAL CREDITS 2025-2026 TUITION*
ON CAMPUS 2 YEARS 36 $22,860
* For full-time course load students. Based on a full course load: 30 credits for undergraduate programs and 18 credits for graduate programs per year.

DEGREE DETAILS

The Master of Science in Big Data Analytics degree is earned by completing the program course requirements of 36 credit hours (12 courses of 3 credit hours), of which 21 credits are core courses and 15 credits are elective courses. To qualify for the Master of Science in Big Data Analytics degree, students must meet all core and concentration elective credit requirements.

Students should meet the following minimum requirements to qualify for a graduate degree:
Minimum Passing Grade Per Course B- (CGPA 3.00)

Total Required Credits 36

  1. Students enrolled in the graduate program must maintain a Cumulative Grade Point Average (CGPA) of at least 3.0 (B) out of 4.0 and earn a minimum grade of not less than 2.7 (B-) out of 4.0 on all courses to qualify to graduate.
  2. The Maximum Time Frame (MTF) for completion of the Master’s program is 54 credits.
  3. A graduate student may transfer up to 9 credit hours earned at accredited institutions.
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PROGRAM OUTCOMES

  1. Understand the theories and methodologies of data science applied to Big Data and Data Mining, including principles, frameworks, and models for transferring, transforming, analyzing, and interpreting data.
  2. Convert a data analytic problem and related information into a proper mathematical, statistical representation, and usable contexts by using appropriate methodologies for transferring, transforming, and analyzing based on attributes of the available datasets.
  3. Apply advanced and intelligent computer algorithms to produce a reliable data model and system for implementing automatic data collection and analysis using computer programming languages for data sciences, such as Python, R, etc.
  4. Demonstrate effectiveness and efficiency of operating and executing computer commandline interfaces and software applications for data organization, manipulation, and presentation, including implementations of security measures and ethical practices for collecting and storing data.
  5. Communicate effectively orally and in writing with technical and non-technical stakeholders, including data collection process and summarization of results in the descriptive, numerical, and visual forms.
  6. Appraise knowledge, skills, and abilities in information technology and data science of big data analytics applying to research and project beneficial to organizations, such as federal or national governments, state and local governments, nonprofits, and industries, in protecting digital resources and infrastructures.
  7. Assess technical skills and knowledge to pursue various professional technology certifications globally recognizable in the industry, such as Dell Associate – Data Science Version 2.0 Certification, Dell Specialist – Data Scientist, Advanced Analytics Version 1.0 Certification, etc.
  8. Understand the role of responsible citizenship in the legitimate use of technology and digital data
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COURSES IN THE DEGREE

Students must earn a total of 36 college credit hours to receive this degree. Of these credit hours, 21 credits are core courses, and 15 elective credits.

In addition, students must meet the following criteria:

  • Students enrolled in the graduate program must maintain a Cumulative Grade Point Average (CGPA) of at least 3.0 (B) out of 4.0 and earn a minimum grade of not less than 2.7 (B-) out of 4.0 on all courses to qualify to graduate.
  • The Maximum Time Frame (MTF) for completion of the Master’s program is 54 credits.
  • A graduate student may transfer up to 9 credit hours earned at accredited institutions.

BIG DATA ANALYTICS:
COURSE LISTING

Core Requirements: 21 Credits (7 Courses)

 

Course Code Course Name Pre Requisite Credit
BGDA 501 Introduction to Big Data   3
BGDA 510 Data Mining CMPS 514 3
BGDA 511 Big Data Analytics CMPS 514 3
BGDA 522 Applied Statistics   3
BGDA 555 Business Intelligence BGDA 522 3
CAPS 623 Internship – $925 Course Fee (Internship Placement) All Cores 3
CMPS 514 Management Information Systems   3

Electives: 15 Credits (Student must choose 5 courses)

Course Code Course Name Pre Requisite Credit
BGDA 513 Artificial Intelligence BGDA 511 3
BGDA 521 Technology Management   3
BGDA 550 Big Data and Hadoop Environment BGDA 511 3
BGDA 552 Big Data Analytics and Cloud Computing BGDA 511 3
CMPS 515 Network Security & Cryptography CMPS 514 3
CMPS 517 Computer Forensics CMPS 514 3
CMPS 524 Computer Networks and Mobile Communications CMPS 514 3
CMPS 530 Machine Learning and Pattern Recognition BDGA 522
or CMPS 516		 3
CMPS 564 Information Security Management CMPS 515 3
MKTG 615 Marketing Analytics BGDA 555 3

* For detailed descriptions of each course, please visit the BAU 2024-2025 Academic Catalog.

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PROGRAM BENEFITS

BAU’s Master of Science in Big Data Analytics leads to career paths in data analysis positions for various industries. The primary benefit of this program is that students gain theoretical knowledge and hands-on experiences in data collection and analysis to execute processes manually and automatically, which will provide them with intensive skills to pursue career positions in data analytics for various types of organizations and businesses.

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CAREER OPPORTUNITIES

The program will prepare students for job positions such as data analyst, database administrator, database developer, data modeler, data scientist, business intelligence analyst, database manager, data warehouse manager, data architect, big data engineer, and data scientist.

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READY TO APPLY?

 

  START DATE DEADLINE TO APPLY
SUMMER SESSION MAY APRIL 1
FALL SEMESTER AUGUST JULY 1
SPRING SEMESTER JANUARY OCTOBER 1
START YOUR APPLICATION NOW (NO APPLICATION FEE REQUIRED!)

OUR PRACTITIONER-DRIVEN TEACHING
WILL PROVIDE YOU A REAL-WORLD EXPERIENCE

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Bintou Lingani, Ph.D.

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Bintou Lingani is the chair of the Department of Business and Economics at Bay Atlantic university, Washington, DC. She graduated with a Doctorate degree in International Economics and Development in 2019 from Howard University. Her research interest focuses on International Trade and Economic Development in Sub-Saharan Africa and less developed Countries in general. Her teaching journey began when she earned a teaching assistantship while pursuing her master’s at Howard University and she continued to work in academia ever since. Bintou Lingani’s professional philosophy revolves around constant learning in an encouraging environment. She uses her positive attitude, her tireless energy, and her expertise to empower students to reach new heights.

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Sean Michael Cox, Ph.D.

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Sean Michael Cox, Ph.D., is the Chair of the Department of Political Science and International Relations at Bay Atlantic University. His area of academic expertise focuses on Comparative Politics and includes specializations in post-Soviet politics, Eastern European and Balkan Politics, Turkish politics, and US politics. Dr. Cox is a Senior Advisor at the Global Policy Institute, a Washington, D.C.-based economics and international affairs think tank. During his career, he has served as Primary Investigator on numerous projects funded by a variety of public and private organizations including USAID, the US Departments of Education and State, the European Commission, NATO, and a number of foundations.

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Dr. Pipop Nuangpookka

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Dr. Pipop Nuangpookka is the Chair of Information Management Science Program and Director of Distance Education at BAU. He started teaching in Computer Science, Information Technology, and Cybersecurity disciplines in 2007. His research interests are Non-Destructive Method of Detecting Hardware Attack, PII Security Controls, Web Server Protection, and Bilingual Translator Programming. He is a co-author of scholarly papers published in the Journal of Computing Sciences in Colleges/ACM digital library, including “Hardware-Tampering Security Risks in the Supply Chain” and “Fileless Malware and Programmatic Method of Detection.

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Oonah Jaja-Wachuku

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Oonah Jaja-Wachuku is the department chair of the General Education program at Bay Atlantic University. She is a double masters’ degree holder in the areas of International Business Management (MBA) and Multilingualism, Linguistics and Education (MA). She has over 10 years of teaching/instructing experience in different parts of the world. Oonah is passionate about teaching and learning and strives to bring creativity, new paradigms and processes to the practice of educating bright minds.
Ms. Jaja-Wachuku is a self-published author and blog writer – a reader, writer and lifelong learner.

Paolo von Schirach

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Paolo von Schirach was appointed President of the Global Policy Institute, GPI, in March 2016. He is also Professor of Political Science and International Relations at Bay Atlantic University BAU in Washington, DC. He served as Chair of PSIR from 2018 until June 2022. His GPI research and BAU teaching focus on contemporary world politics and economics, international trade, energy, competition policies, and the role of innovation in economics.

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