Program of Study
The Master of Science in Business Analytics (MSBA) program consists of 10 core courses (30 units) designed to equip students with advanced analytical skills and business intelligence expertise. Structured as a 16-month cohort-based program, the curriculum covers Python programming, machine learning, data visualization, business intelligence, and Generative AI applications. Through hands-on projects and a capstone experience, students gain practical expertise in leveraging data for strategic decision-making across industries.
The courses below provide insight into the MSBA curriculum:
MSBA 500 Business Analytics Fundamentals:
Business Analytics Fundamentals is a foundational course within the Master of Science in Business Analytics program, designed to provide students with a comprehensive understanding of key concepts, tools, and techniques in business analytics. This course covers topics such as data-driven decision making, analytical tools, business functions, interpretation of results, and ethical considerations in business analytics. Students will also engage in practical case studies to apply their learning to real-world scenarios.
MSBA 510 Python Programming for Business Analytics:
This introductory course equips students with foundational knowledge in Python programming tailored to business analytics applications. Students with or without prior programming experience will learn essential Python concepts including basic programming structures, functions, classes, and delve into powerful libraries like NumPy, Pandas, and Matplotlib, for data analysis and visualization. Designed for beginners with or without prior programming experience, this course serves as a springboard for advanced topics such as Machine Learning.
MSBA 520 Foundations of Databases & SQL Programming:
This course introduces students to the foundational principles and practices of database and data management. It covers database design, data modeling, SQL for data manipulation and definition, advanced data analytics techniques, and the latest trends in cloud databases. Through hands-on projects and activities, students will gain practical experience in designing and managing databases that drive business analytics.
MSBA 530 Business Statistics for Data Analytics:
The Business Statistics course is an essential component of the MS in Business Analytics
Program. This course equips students with a solid understanding of statistical methods
and tools required for data-informed decision-making. Topics covered include descriptive
statistics, probability, statistical inference, hypothesis testing, and regression
analysis, all of which are fundamental in the field of business analytics. This course
acts as a bridge between foundational and advanced courses, preparing students for
the complex analytical challenges
they will encounter.
MSBA 540 Machine Learning for Business Applications
Machine Learning for Business Applications is a fundamental course designed to equip students with the knowledge and skills needed to apply machine learning techniques to solve real-world business problems. This course focuses on essential topics such as linear regression,logistics regression, k-nearest neighbors, unsupervised learning (Principal Components and Clustering Methods), model and variable selection, and nonlinear prediction methods. Students will gain hands-on experience in implementing machine learning algorithms and interpreting their results within the context of business analytics.
MSBA 550 Business Intelligence and Big Data Analytics
The Business Intelligence (BI) and Big Data Analytics course offers a deep dive into BI fundamentals and the nuances of Data Warehousing design and environments. Learners will engage with the processes of Data Extraction, Transformation, and Loading (ETL) and how to analyze and visualize data in the data warehouse. The latest Big Data technologies and analytics tools will be introduced. The pivotal role of Data Governance in digital transformation will be covered. Real-world case studies to showcase industry applications will be discussed. By its conclusion, students will not only be proficient in extracting valuable insights from extensive data sets but will also foster a robust data-driven and analytical mindset crucial for business analytics.
MSBA 560 Data Visualization & Data Storytelling:
This course focuses on principles, tools, and applications for creating compelling visualizations and telling impactful stories with data. Students will explore critical analysis of visualizations, design principles, and collaborative storytelling techniques. Emphasizing practical skills, the course prepares students to communicate data analytics results effectively.
MSBA 570 Generative AI and LLM Tools and Applications
This course emphasizes practical applications and tools in the realm of Generative Artificial Intelligence (AI) and Large Language Models. Students will grasp foundational concepts, architectures for GAI and LLMs. Prompt engineering for both textual and visual content generation will be studied. Learn how to harness the power of Large Language Models for business analytics. Delve into the ethical landscape, exploring potential risks and safeguards associated with Generative AI in a business context. Critically analyzing real-world case studies to shed light on the practical challenges and benefits of generative AI in today's dynamic business environment.
MSBA 580/BUS536 Special Topics in Business Analytics
This course offers an in-depth analysis of current topics in business analytics, with the content varying each semester. Students will explore emerging trends, technologies, and applications in the rapidly evolving field of business analytics.
MSBA 590 Business Analytics Capstone Project
In this capstone course for the MS in Business Analytics Program, students embark on a conclusive journey that synthesizes and applies the knowledge and skills acquired throughout the program. Engaging in a real-world and hands-on project, students apply full data analytics lifecycle methodology to manage the project. Whether presenting comprehensive findings to clients or compiling a professional portfolio, students are positioned to showcase their proficiency in practical business analytics applications.
Your Program Roadmap:
- Program Roadmap (16 months, 30 units)
- Fall Year 1: Business Analytics Fundamentals, Python, SQL Databases
- Spring Year 1: Business Statistics, Machine Learning, Special Topics
- Summer: Generative AI, Big Data
- Fall Year 2: Data Visualization & Storytelling, Capstone Project
Please note that course names, numbers, instructors, and descriptions are subject to change. For the latest information, refer to the university catalog.