Online Masters in Business Analytics Curriculum

Curriculum Details

30 total credit hours required

The online M.S. in Business Analytics features a career-connected curriculum that explores advanced business analytics concepts. Throughout the program, you’ll engage in experiential learning that involves an array of analytics tools, including SQL, Python, R, and Tableau. Our online MSBA degree also helps you prepare for International Institute of Business Analysis (IIBA) certifications, including the Certification in Business Data Analytics (CBDA).

Complete the program’s 30 credit hours in 1.5 years or sooner with transfer credits. You can transfer up to 15 eligible credits, accounting for up to half of the program’s courses.

Core

Credits

DAT 517 Machine Learning for Business Analytics Credit Hours: 3

Covers machine learning techniques and their application in business, using tools like Python, R, and Scikit-learn. Topics include supervised and unsupervised learning algorithms such as regression, classification, and clustering. Emphasis is placed on predictive modeling, customer segmentation, and demand forecasting for practical business applications.

DAT 527 Business Analytics and Cloud Platforms Credit Hours: 3

Focuses on the processing and analyzing large-scale datasets using cloud computing platforms like AWS, Google Cloud, and Azure. Topics include distributed computing frameworks like Hadoop and Spark, with practical applications in cloud-based data storage, processing, and real-time analytics.

DAT 537 Business Process Automation and Optimization Credit Hours: 3

Examines the use of automation tools such as UiPath, Automation Anywhere, and Blue Prism to streamline and optimize business processes. Case studies highlight the impact of automation onreducing manual interventions, improving operational efficiency, and driving cost savings in various industries.

DAT 557 Data Mining and Text Analytics Credit Hours: 3

Delves into data mining techniques including association rule mining, decision trees, and clustering, along with text mining using RapidMiner, SAS, and NLTK. Emphasis is placed on extracting patterns, trends, and insights from large datasets and unstructured text, supporting decision-making in areas such as marketing, customer service, and product development.

DAT 560 Prescriptive Analytics and Optimization Techniques Credit Hours: 3

Covers optimization techniques for prescriptive analytics, using tools like Gurobi, CPLEX, and Excel Solver. Includes decision-making under uncertainty, linear programming, and simulation-based approaches, with practical applications in supply chain optimization, resource allocation, and production scheduling.

DAT 565 Predictive Analytics and Programming Credit Hours: 3

Focuses on predictive analytics methodologies using tools like Python and R, including time series analysis, neural networks, and regression modeling. Emphasis is placed on forecasting trends and behaviors in areas such as financial forecasting, inventory management, and customer analytics.

DAT 570 Data Governance, Ethics, and Security Credit Hours: 3

Examines best practices for data governance, ethical data management, and ensuring data security. Tools like Collibra, Informatica, and DataRobot are used to ensure data quality and regulatory compliance, with discussions on GDPR, data privacy, and the ethical implications of data analytics in business.

DAT 575 Real-Time Data Analytics and IoT Credit Hours: 3

Explores real-time data analysis using Kafka, Apache Flink, and Azure Stream Analytics. Focus is on analyzing streaming data from IoT devices and applying real-time insights to business decision-making in manufacturing, transportation, and smart cities.

DAT 580 AI-Driven Business Strategies Credit Hours: 3

Covers the integration of artificial intelligence into business strategies using tools like TensorFlow and Keras. Focuses on leveraging AI models to automate decision-making, enhance customer experiences, and drive innovation in business operations. Topics include deep learning, AI ethics, and applying AI to gain competitive advantages.

DAT 590 Advanced-Data Analytics and Visualization Tools Credit Hours: 3

Explores the use of advanced data analytics platforms such as Tableau, Power BI, and D3.js for creating interactive visualizations and dynamic dashboards. Emphasizes transforming raw data into actionable insights and applying design principles for effective visual communication. Focus is placed on data storytelling and presenting complex analytics results to diverse audiences.

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