Business Analytics

In This Section

Name	Title	Credits	School
BUSA 301	Data Management & Visualization for AI	3	School of Management
This course focuses on AI-driven data curation, covering key aspects from data acquisition and preparation to advanced AI implementation. Students will learn to leverage AI tools for collecting diverse data (including textual sources), perform AI-assisted cleaning and quality assessment, and conduct feature engineering for model training. Emphasis is placed on using AI-enhanced visualization tools to create impactful representations that reveal business patterns and trends. Through hands-on projects, students will apply these techniques to solve real-world challenges and effectively communicate analytical insights. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 305	Python for Business Analytics	3	School of Management
This course discusses applications of business analytics using Python to strengthen data-driven decision-making across various business functions. Students will explore AI-powered tools to enhance data mining, predictive analytics, and decision-making processes. Through practical projects, students will apply these techniques to real-world business challenges using AI-assisted solutions, for better decision-making. Prerequisite Course(s): Prerequisites: QANT 201 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 310	Database Management Systems	3	School of Management
This course provides an introduction to contemporary database management systems, with a focus on AI-enhanced database technologies. The students will learn current developments in database theory and practice. They will design, implement, and manage databases while using AI tools for query optimization, data modeling, and performance tuning. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 315	AI-Enhanced Business Analytics	3	School of Management
This course equips students with the analytical mindset and technical skills needed to leverage large language models (LLMs), agentic AI, and other generative techniques, to create value across different business disciplines. Students will develop predictive models, design generative AI solutions, and apply end-to-end Generative AI pipelines to a variety of business disciplines. The course emphasizes the practical implementation of AI in business decision-making. Prerequisite Course(s): Prerequisites: QANT 201 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 325	Applied Statistical Modeling and Quantitative Analysis	3	School of Management
This course develops critical statistical thinking and quantitative modeling skills essential for business analytics and artificial intelligence applications. Students will solve real-world problems within various business domains such as operations management, marketing, and finance using quantitative analysis. This course emphasizes the application of statistical methods to field-specific challenges within business contexts, demonstrating individual accountability through collaborative analytical projects. Prerequisite Course(s): Prerequisites: QANT 201, QANT 300 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 410	Web and Social Media Analytics	3	School of Management
This course covers applications of business analytics in web and social media, focusing on AI-powered tools for sentiment analysis, text mining, and web performance optimization. Students will use Python for AI-enhanced data mining and learn to leverage AI-driven insights to inform strategic decision-making in practical business problems. Prerequisite Course(s): Prerequisites: BUSA 305 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 425	Collaborative AI Analytics Practicum	3	School of Management
A hands-on course where students work collaboratively with external partners on real-world AI and analytics projects. Emphasizes individual accountability in team settings, effective communication of complex findings, and meaningful feedback on collaborative project work. Students will engage with industry partners to solve authentic business problems using AI and analytics. Prerequisite Course(s): Prerequisites: BUSA 315 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 0-0-3
BUSA 460	Advanced AI & Analytics Capstone Project	3	School of Management
A culminating experiential course where student teams tackle complex business problems using integrated analytics and AI techniques. Projects require mathematical analysis, external resources, technology integration, and communication of findings. Students will demonstrate mastery of all program learning goals while producing solutions that inform management policy. Prerequisite Course(s): Prerequisites: BUSA 315, BUSA 425 or Internship Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3