The Master of Science in Business Analytics combines technical skills, analytic frameworks, and business insights. It’s designed for future leaders to make data-driven decisions, delivering strategies and decisions through an integrated approach to operations, finance, programming, machine learning, and AI.
Highlights
Data Analytics Skills
Cutting-edge data analytics in Probability and Statistics, Programming, Data Management and Visualization, and Machine Learning.
Business Principles
The overview of key management principles spans across Finance, Accounting, Marketing, and Operations.
Leadership Essentials
Business leadership essentials emphasize data-based decision making within Competitive Strategy, Leadership, and Building High Performing Teams.
Practical Experience
Gain practical experience through a hands-on capstone project with companies, and guest lectures from practicing experts in the field.
Courses
You will gain business and analytical skills to develop effective strategies and recommendations for business intelligence. Find out how each course in our integrated and comprehensive curriculum will help you to become an effective Business Analyst.
In this course you will learn the basics of Financial Accounting, Managerial Accounting, and Finance. Expert faculty teach how transactions impact a firm’s financial statements, analyze those statements, make informed decisions, and evaluate and incentivize managers. In the accompanying project, you will use R to create a portfolio of 30 firms with mixed long and short positions by comparing earnings quality using the accrual metric as a statistical signal from Excel data. This hands-on approach integrates financial analysis with practical portfolio management.
This class equips you with essential tools to create and lead high-performance teams. You will learn to apply research-backed principles to assemble teams capable of sustained excellence in achieving meaningful and challenging objectives. This course’s practical approach positions you to drive team success in any professional setting, making the knowledge and skills you gain invaluable assets for your career growth.
This course provides a comprehensive understanding of a firm’s strategy, including how it compares to but differs from related concepts such as business models. We examine the business holistically from the perspective of the firm’s primary strategist, the Chief Executive Officer. This course enhances students’ abilities to align their efforts with their organization’s core priorities and equips them with the language and concepts necessary to attain a competitive advantage in the workplace and propel their careers forward.
In the Operations Management Analytics course, you will gain a deep understanding of critical operational issues and learn advanced analytical techniques essential for planning, managing, optimizing, and executing the production and delivery of goods and services, particularly in high-tech industries. Through a mix of lectures, case studies, and practical applications, you will develop strong quantitative and problem-solving skills that are highly valued by employers. This course will prepare you to tackle real-world operational challenges, focusing on critical areas such as capacity planning, service operations, inventory management, and supply chain analytics.
In this class, you will learn how to develop decision-support models using quantitative analysis tools, including linear programming, decision analysis, and simulation. Upon completing this class, you will thoroughly understand these concepts, develop hands-on experiences in building decision support models in Excel spreadsheets, and gain essential skills to derive managerial insights from complicated mathematical modeling and analysis.
Upon completing this course, you will be equipped to utilize probability models and inferential statistics for robust business analysis. Through various hands-on activities, including working with real-world big data, you will apply these concepts and explore the integration of AI tools to enhance your analytical capabilities.
This course explores the integration of generative AI with modern programming languages to glean business intelligence. Students will learn how AI can augment traditional programming tasks, the new paradigms introduced by AI-driven development, and practical skills for leveraging AI in programming. The course encompasses general concepts and techniques, including Python basics, data visualization, and business decision-making.
In this course, you will learn how to use SQL queries to retrieve information from a relational database. SQL is one of the most important tools in an analytics professional’s toolkit. After completing the course, you will be able to use SQL to generate and present valuable insights from real-world data.
The Customer Analytics course provides a 360-degree perspective on leveraging data to improve customer interactions and relationships. It covers key strategies to acquire, grow, and retain customers and teaches you to create customer value metrics. You’ll explore models tailored to customer-facing data using R and understand how AI can enhance these foundational models. This course equips you to make data-driven decisions around the customer lifecycle, benefiting both internal and external customer interactions in any industry.
In this course, you will learn how to optimize decisions for the four Ps of marketing: Product Design, Pricing, Promotion and Advertising, and Placement. The curriculum includes economics, statistics, and machine learning principles and applies them to real-world case studies from various contexts, including retailing, digital marketing, and mobile advertising. This course will prepare you for business analysts, data scientists, and technical product management roles.
In this course, students learn to optimize online advertising, email marketing, and mobile marketing strategies through an analytics-centered approach, focusing on experimentation and data-driven decision-making. The course provides hands-on skills in identifying and analyzing marketing problems using modern statistical, econometric, and machine learning methods in R, essential for careers in technology, consulting, marketing, or entrepreneurship. By developing these skills, students gain the competency to manage marketing analytics teams and make informed decisions to achieve digital marketing outcomes.
In this course, you will develop essential skills in using quantitative tools and software, including Python and R, to gain insights from business data across various industries. You’ll work on case assignments and a final project applying descriptive analytics and statistical modeling to real-world scenarios, equipping you with the ability to critically evaluate data and identify opportunities for analytics in operations, marketing, finance, and more. While coding is involved, the focus is on interpreting and modifying code to derive insights, preparing you to confidently lead analytics initiatives in the workplace and become a data-savvy manager.
In this class, you will learn the basics of machine learning. The course provides a strong statistical foundation rooted in A/B testing and delves into concepts including regression, classification, the bias-variance tradeoff, regularization, and neural networks. Students will use current vision and language AI tools and evaluate the tradeoffs and societal implications of using these methods. By the end of the course, you will be familiar with using Python tools such as SKLearn and Pytorch to build predictive models.
This pivotal course bridges the gap between academic knowledge and industry application. Distinguished business analytics professionals provide insights, expertise, and practical wisdom in a classroom setting, giving students a unique opportunity to hear from leaders in the field.
In this course, you will learn how to make pricing decisions using a data analytical approach. Students work with real-world data and code up models in R to optimize pricing decisions in many different business applications and contexts. Upon completing the course, you will be able to design and analyze price experiments, use sales and price data for demand modeling and optimal pricing, and choose between different pricing structures like uniform pricing, targeted pricing, product line pricing, and bundled pricing in various markets.
The course develops the critical skill of uncovering key insights in data and presenting them convincingly to diverse audiences. You’ll learn to create and critique various chart types, design interactive dashboards, and craft compelling data stories with narrative arcs. Using tools like Tableau, Power BI, or Google Data Studio, you’ll gain hands-on experience directly applicable to today’s data-driven business world. This course will empower you to turn raw data into powerful visual stories, a skill increasingly vital in the age of AI and big data analytics.
The MSBA Practicum class connects students with companies to collaborate on business analytics projects, providing first-hand experience and skill training in demand by today’s employers. Students work in teams using analytics, machine learning, AI, programming, and data visualization tools to answer current and vital business real-world business questions. We partner with leading firms like Microsoft, GM, Tableau, Salesforce, the US Army, and a host of firms active in Electric Vehicle technologies, Climate Change Analysis, and AI deployment.