Curriculum

The innovative curriculum consists of rigorous courses that will help build your capabilities in technical, analytical, and operational areas to prepare your career with modern computer analytics and management skills.

This STEM designated 4-semester fully online or hybrid program is transfer-friendly for students with any AS-T degree. Students with an AS-T in computer science will be able transfer all 60 lower division units to this program. For students with an AS-T or AA-T, the program requires only two (2) Lower Division core courses:

  • MATH 130 Calculus I (or equivalent course from Community College)
  • CS/MATH 211 Discrete Structures (or equivalent course from Community College)

After admission, students may complete the LD core courses online through California Virtual Campus. Special sessions of the above courses will be offered to help admitted students fulfill the prerequisites

Throughout this degree completion program (with 60 upper-division units), students will complete core courses (33 units), analytics concentration courses (18 units), and elective breadth courses (9 units) taught by faculty specialized in computational analytics, information systems, marketing analytics, supply chain analytics, statistics, as well as computer science. The blending of these course types provides students with a holistic skill set and allows them to focus on a wide range of topics including in-depth business applications using emerging computational algorithms such as AI, ML, information systems, marketing intelligence, or management science.

Our online learning tools bring you face-to-face with classmates and professors who expose you to real-world business challenges. You will learn from Silicon Valley professionals who have experience leading analytics teams in real-time during live, online classes and completely engaging, interactive coursework that reflects the latest thinking in analytical tools and methods.

 

 

Qualified students may complete 30 units MBA core courses, full-time (in 9 months) or part-time (while working), to receive MBA Degree in Analytics for Manager Concentration

Earn an AACSB-accredited MBA Degree after Completing 30 Units of MBA Core Courses

Students are now able to earn an AACSB-accredited MBA degree from the College of Business and Economics at CSU East Bay for 12 units fewer credits. Qualified students may complete 30 units of MBA core courses, full-time (in 9 months) or part-time (while working), to receive an MBA Degree in Analytics for Manager Concentration. For up to five years after graduating, students may take advantage of this opportunity and apply for this online MBA program. This opportunity allows students to develop skills in an additional area of interest can help set them apart in the job market and expose them to a wider variety of career opportunities.

The following 30 units of MBA core courses are required to complete this accelerated MBA program:

  • ACCT 604 Financial Accounting
  • ECON 606 Managerial Economics
  • FIN 605 Corporate Financial Management
  • MGMT/MKTG 601 - Leading People and Organizations; Managerial Communication
  • MGMT 602 Business Analytics for Managers
  • MGMT 603 Managing Complex Issues in Global Context
  • MGMT 608 Operations and Supply Chain Management
  • MGMT 609 Negotiation and Conflict Resolution
  • MKTG 607 Marketing Management
  • MGMT 693 Strategic Management Capstone (Project)


The following four MBA concentration elective courses (12 units) are blended with B.S. in Business
Analytics program:

  • BAN 602 Quantitative Fundamentals for Analytics (replaced with BAN 315 Data Analysis with Python
    II)
  • BAN 610 Database Management and Applications (replaced with BAN 331 Database Management
    and SQL)
  • BAN 630 Optimization Methods for Analytics (replaced with BAN 320 Optimization and Simulation
    for Business Applications)
  • BAN 674 Machine Learning for Business Analytics (replaced with BAN 340 Machine Learning for
    Business Applications)

Faculty teaching B.S. in Business Analytics program are accomplished scholars with extended academic and industrial connections with companies in Silicon Valley and San Francisco Bay Area. Our dedicated faculty are passionate about working with their students. We look forward to getting to know you, mentoring you, and supporting your academic and professional journey.

 

Faculty Name 

Degree and Institute

Area of Interest

Courses Taught in Business Analytics

Bryant Cassidey

Ph.D., University of Alabama

Operations and Supply
Chain Analytics

Decision Science,
Optimization for
Analytics

Varick Erickson

Ph.D., University of California, Merced

Computer Science

Data Structures and Algorithms

Ivan Fedorenko

PhD, Bentley University

Marketing Analytics

Digital Media Analytics
Customer Analytics

Yuanyuan Gao

PhD, University of Utah

Information System

Big Data and Technology
Data Warehousing and BI

Jia Guo

PhD, University of Alabama

Supply Chain Analytics

Data Analytics,
Optimization for
Analytics,
Machine Learning,
Operations Analytics
Business Analytics for
Managers

Yi He

PhD, University of Hawaii

Marketing Analytics

Mobile Marketing and
AI, Consumer Analytics

Matt Johnson

Ph.D., College of William and Mary

Computer Science

Artificial Intelligence

Inkyu Kim

Ph.D, Michigan State University

Information System

Tech fundamental for
Analytics, Data Mining,
Deep Learning

Somak Paul

PhD, Ohio State University

Statistics, Operations
Management, Supply
Chain Analytics

Quantitative
Fundamentals for
Analytics, Optimization
Techniques

Steve Peng

PhD, York University

Operations Analytics

Data Visualization and Reporting

Zinovy Radovilsky

Ph.D., Scientific Research
Institute of Operations
Management

Operations/Supply Chain
Management and
Business Data Analytics

Data Mining
Optimization Methods
for Analytics
Time Series Analytics
Business Analytics for
Managers

Balaraman Rajan

PhD, University of Rochester

Operations Management
and Healthcare Analytics

Data Mining, Healthcare
Analytics

Surendra Sarnikar

PhD, University of Arizona

Information Systems,
Healthcare Analytics

Deep Learning, Data
Engineering and BI

Lan Wang

PhD, University of Florida

Operations Management
and Information System

Data Analytics in Python
Operations Analytics

Chongqi Wu

Supply Chain Analytics

Jiming Wu

PhD, University of Kentucky

Information System, Big
Data Analytics, Artificial
Intelligence

Capstone Project, Big
Data, Database, and Java
and Python Programming

Peng Xie

PhD, Georgia Institute of

Technology

Information System

Blockchain and Smart Contract

 

 

Upper Division Course Descriptions - Total 60 Units