I do my best to align CS curricula with the real world, based on three decades of hiring, mentoring, and leading graduates in industry.
A 13-week foundation course in neural networks with PyTorch, required of every HIT CS student. Lab-first and project-based, designed for work with an AI assistant through a Build, Predict, Explain model and no written exams.
A 13-week Year 3 advanced course on building and running AI systems in production: DevOps, DataOps, MLOps, LLMOps, and AgentOps, taught end to end through one running HIT project.
A 13-week graduate course on generative modeling, spanning variational autoencoders, diffusion models, and world models, taught at HIT.
A 13-week graduate course on large language models and agentic AI, covering modern LLM architectures, alignment, tool use, and multi-agent systems, taught at HIT.
An advanced 13-week course on architecture, design patterns, API contracts, persistence, and AI-enabled enterprise systems, with one running project and no written exams.
As Head of the Software Engineering track at HIT, I developed a new CS curriculum proposal centered on Innovation-First Learning principles.
Six third-year specialization tracks built on a shared CS foundation at HIT, each turning broad CS knowledge into job-ready expertise with a portfolio.
I established and led an industry advisory board to define practical readiness profiles for graduate roles, including AI engineer and full-stack developer tracks.
Innovation-First Learning bridges traditional CS education and current AI practice through deep theory, modern tools, and project work.
