Industrial AI Application and Practice

Catalog description

This course bridges the gap between AI theory and real-world deployment by immersing students in the practical application of Artificial Intelligence across industrial sectors such as manufacturing, healthcare, logistics, finance, and agriculture. Students will analyze case studies, evaluate deployment architectures, and work with real or simulated datasets to implement AI solutions that meet performance, security, and compliance requirements in enterprise environments. Topics include production-grade model development, MLOps workflows, edge-AI integration, ethical and regulatory considerations, model monitoring and retraining, and the use of APIs and cloud platforms for scalable deployment. Emphasis is placed on building AI systems that are robust, explainable, and aligned with organizational goals. By the end of the course, students will have delivered an AI project proposal and prototype aligned with an industry-specific use case, preparing them for roles in AI consulting, system integration, and applied research.