Online Master of Science in Business Analytics Courses
Curriculum Details
- 10 courses
- 30 credits
- 8-week course duration
USC Upstate’s business analytics master’s online program is designed to provide a rigorous, career-focused education that fits your schedule. You can graduate in as few as 18 months with 8-week courses that cover data analytics, AI, predictive modeling and business strategy.
The program offers multiple start dates throughout the year, giving you the flexibility to begin when it works best for you. Through hands-on projects, mentorship and practical applications, you’ll build the credentials and experience needed to excel in high-demand analytics roles.
Core
Credits
Statistical estimation methods using R. Topics will include basic programming in R including simple graphs, data input and output, basic statistical concepts including probability theory, linear regression models, general linear models, piecewise linear regression, logistic regression, and factor analysis including exploratory and confirmatory analysis.
The fundamentals of data mining, data management, and data warehousing. Topics include design and querying of relational databases, design, setup, and use of data warehouses and various data and text mining methodologies.
Contemporary and comprehensive treatment of modern time series and empirical prediction. Topics include autoregression, moving average, ARIMA processes, volatility models, cluster analysis, and structural equation modeling.
Case-based approach to understanding the role and impact of data analytics on business performance. Data cleaning and data quality, analytics project life cycle, machine learning, fundamentals of good visualization, effective technical communication strategies, and ethical frameworks for business analytics are explored.
The essential and practical skills in visualization, including computer graphics, visual data representation, physical and human vision models, numerical representation of knowledge and concepts, animation techniques, pattern analysis, and computational methods. Various software tools will be studied including R, gg-plot2, and Tableau 8.
Skills and knowledge necessary to model situations where uncertainty is a major factor. Models may include decision trees, Monte Carlo simulation, discrete event simulation, and stochastic optimization, along with applications for solving a wide variety of common business problems.
Solving business problems from data collection and model construction through analysis and presentation of results to recommendations for specific business decisions. Commercial and open source software tools will be used to build models and conduct analyses.
Electives (Choose 3 Courses)
Credits
Applications of optimization through case studies and computer exercises to provide insights into business and economics. Statistical methods will include linear, network, integer, and nonlinear optimization using Excel and SAS/OPTMODEL.
Collect, process and analyze financial data. The emphasis will be on analyzing firm valuation and firm and industry performance; forecasting and managing firm growth; evaluating business projects and major corporate decisions; and researching risk and returns of stocks, bonds, and portfolios.
Fundamentals of applying data analytics approaches in accounting and auditing. Topics include using the IMPACT model in accounting and auditing; designing and querying relational database using the REA (resource/events/agents) data model and SQL; understanding strategic and emerging technologies in accounting relating to data analytics; and applying auditing analytics and modern auditing concepts to aid in sampling and risk assessment.
Ethical and legal theories that have led to various regulations, including antitrust, workers’ compensation, social security, employment law, taxation, and environmental compliance. Topics will include the uses of analytics to support the overarching theories and regulations.
Quantitative modeling tools and techniques used to solve problems faced in modern supply chains such as forecasting demand, determining the capacity of a manufacturing line, and optimizing the production operation.
Principle and practical issues while effectively integrating data analytics topics using R/Python. Topics will include data preparation, missing data, lists, functions, and loops.
Methods and tools to collect, analyze, and report website usage data by visitors, emphasizing the nature of the visits to websites and visitors’ demographics. Concepts, tools, tutorials, and case studies that business managers need to extract and analyze the seven layers of social media data, including text, actions, networks, apps, hyperlinks, search engine, and location layers will be emphasized.
Developing analytical methods and applying statistical and mathematical tools to predict consumer behavior. Formal models to analyze how and when customers make product purchase decisions, configure new products, develop market segments, forecast market share, and determine optimal pricing strategies will be introduced.
Select subjects and current trends in the social, cultural, political, and technical issues associated with business analytics.
Request More Information
Complete this form to receive information about coursework, admissions, tuition and more.