Master’s Programs — AI & Emerging Technologies

End-to-end ML + GenAI, from data to production systems

• Build reliable ML pipelines with strong data quality foundations
• Train, evaluate, and debug models using robust methodology
• Apply GenAI patterns (RAG, agents, guardrails) with measurable KPIs

Applied analytics for factories, supply chains, and operations

• Model industrial processes and define actionable KPIs
• Build analytics workflows from raw data to decision dashboards
• Forecast demand/throughput and detect anomalies

Modeling + engineering to ship reliable ML features

• Build robust ML baselines and iterate fast with clean experiments
• Design inference pipelines with performance & reliability in mind
• Deploy services and manage versioning correctly

RAG, agents and evaluation — build GenAI that actually works

• Build RAG systems with evaluation-driven iteration
• Implement safety guardrails and quality checks
• Create stakeholder-friendly demos and documentation

Deploy, monitor and iterate on real AI systems

• Containerize and deploy model services
• Track experiments and model versions
• Define monitoring signals and retraining triggers

Business-first AI: ROI, governance and delivery execution

• Frame AI use cases, define success metrics, and estimate ROI
• Manage delivery: risks, stakeholders, and iterative milestones
• Build a governance mindset: quality, security, compliance basics