Intro to Business Analytics ▸

Coding for Analysis ▸
Syracuse University micro-credential*

Intro to Data Decision-Making Using AI ▸
Syracuse University micro-credential*

Applied AI ▸
Syracuse University micro-credential*

Project Management ▸
Syracuse University micro-credential*

*A focused credential that demonstrates mastery in a specific skill.

AI in Business Capstone

This capstone course serves as the culminating experience in the AI in Business program, providing students with the opportunity to apply their acquired artificial intelligence and business analytics skills to real-world challenges. Working in close collaboration with faculty and industry partners, students will undertake either a comprehensive AI implementation project for an existing organization or develop an AI-driven business venture. The course runs concurrently with Business Analytics III, allowing students to leverage advanced analytics techniques in their capstone work while receiving structured guidance and feedback from faculty. This hands-on experience enables students to demonstrate mastery of the data analysis, artificial intelligence, data systems, and business principles taught throughout the curriculum through practical application in their chosen domain.

Core Topics
  • Project Definition and Planning
    • Assessment of organizational or market opportunity for AI implementation
    • Development of project scope, objectives, and success metrics
    • Creation of detailed project plan including technical requirements
    • Integration planning with Business Analytics III coursework
    • Selection of appropriate AI tools and methodologies
  • Technical Implementation and Development
    • Data collection, preparation, and system architecture setup
    • AI model development and testing
    • Integration of business analytics techniques from concurrent coursework
    • Iterative refinement based on stakeholder feedback e. Documentation of technical processes and decisions
  • Business Integration and Validation
    • Implementation of AI solution in business context
    • Performance testing and optimization
    • Development of monitoring and maintenance procedures
    • Business impact analysis and ROI calculation.
    • Risk assessment and mitigation strategies
  • Project Finalization and Presentation
    • Refinement of technical implementation
    • Creation of comprehensive project documentation
    • Development of deployment or go-to-market strategy or “go, no-go” decision, with evidence of critical thinking and analysis behind the ultimate decision
    • Preparation and delivery of final presentation