Program Requirements
Foundation Courses – 9 credits
Core Courses – 15 credits
Course Code : BU 605
Course Description :
This course provides an introduction to business analytics with a focus on descriptive analytics, data visualization, and exploratory data analysis. Students will learn how to gather, clean, and summarize business data to extract meaningful insights. Using tools such as Excel, SQL,
Python, Tableau, or Power BI, students will create compelling visualizations to support data-driven decision making. Emphasis will be placed on understanding business trends, identifying key performance indicators, communicating findings effectively and addressing the ethical implications of data usage. Real-world case studies will be used to apply analytical concepts to business problems.
Credit : 3 – 3
Course Code : BU 615
Course Description :
This course introduces students to the dynamic field of predictive analytics, providing essential tools and techniques for modeling and forecasting business trends. Students will delve into statistical and machine learning approaches such as time series analysis, regression models, and classification techniques. Throughout the course ethical considerations will be integrated into each topic, examining the potential impacts of predictive modeling on individuals and society Students will learn how to anticipate customer behavior, demand fluctuations, and market trends by applying predictive models to real-world business scenarios, while critically evaluating the ethical implications of their analyses. Hands-on assignments will involve working with various analytical software to build, test, and validate predictive models, incorporating ethical best practices in data handling, model development, and interpretation.
Credit : 3 – 3
Prerequisites :
BU 605
Course Code : BU 618
Course Description :
This course dives into prescriptive analytics, emphasizing optimization techniques and data-driven decision-making, allowing students to turn data into value for the organization. Students will explore mathematical programming, simulation modeling, and artificial intelligence applications to enhance business performance. Key topics include linear programming, Monte Carlo simulations, and machine learning for business decision-making. By applying these techniques to areas such as supply chain management, pricing strategies, and financial portfolio optimization, students will develop models that recommend optimal solutions for complex business challenges. The course culminates in a real-world capstone project, where students apply prescriptive analytics to solve a business problem.
Credit : 3
Prerequisites :
BU-605
Course Code : BU 621
Course Description :
Explores business intelligence architectures, data warehousing, and big data technologies essential for modern analytics environments. Students design Extract, Transform, Load (ETL) processes, build dimensional data models, and work with distributed computing frameworks. The course covers both traditional business intelligence systems and modern big data platforms including Hadoop, Spark, and NoSQL databases. Topics include data warehouse design, OLAP and multidimensional analysis, ETL, process implementation, real-time data streaming, cloud-based analytics platforms, and the integration of business intelligence into organizational decision-making. Students gain practical experience with SQL Server Integration Services, Apache Hadoop ecosystem, Apache Spark, and cloud platforms such as AWS and Azure.
Credit : 3