What You’ll Learn

Design modern software systems

Build smarter with AI

Improve developer velocity and productivity with AI-assisted coding, testing, and refactoring - without sacrificing code quality, security, or ownership.

AI engineering with LLMs

Work with large language models, agents, and multimodal systems. From model selection to orchestration, evaluation, and real-world constraints.

Programming at scale

Modern approaches to writing, structuring, and evolving large codebases. Languages, frameworks, APIs, and patterns that hold up as systems grow.

Production AI done right

Move beyond demos to resilient, observable, production-grade AI systems, considering latency, cost, failure modes, and operational realities.

Data foundations for modern apps

Build data pipelines and platforms that AI systems actually rely on. From structured data to unstructured, vector-based workflows.

Ship reliably and continuously

CI/CD, automation, and platform strategies that enable fast, safe delivery. Built for teams shipping software every day.

Run & operate at scale

Observability, reliability, and incident response for complex systems. Including operating AI and classic workloads side by side.

Test, validate, maintain quality

Modern testing and validation for distributed and nondeterministic systems. Ensuring confidence as software and AI evolve continuously.

Secure software by design

Reduce risk across code, dependencies, APIs, and supply chains. Security practices that integrate into modern builder workflows.

Lead engineering teams in the AI era

Build teams that thrive as tools, roles, and workflows change. From developer productivity to sustainable engineering culture.

Technology strategy in a changing world

How AI, regulation, sovereignty, and platform choices shape long-term decisions. For tech leaders balancing innovation, risk, and responsibility.