Generative AI Engineering & Agentic Systems
Flagship engineering programme focused on production-grade LLM applications, retrieval systems, evaluation, AI agents, safety and deployment.
At a glance
More than course content.
These programmes are designed as high-touch cohort experiences for learners investing in substantial career or leadership transformation.
Live cohort learning
Structured faculty sessions, workshops and applied discussions across the six-month journey.
Mentor reviews
Regular review points for projects, technical decisions, business cases and capstone progress.
Applied portfolio
Multiple business-facing outputs culminating in an enterprise-grade capstone or transformation roadmap.
Career / leadership lab
Professional positioning, executive communication and decision-quality development matched to the track.
Programme fee shown is the proposed launch fee and can be edited in the Admin Console before enrollment opens.
Who should enroll
Software engineers, data professionals, automation specialists, AI product builders and technical managers who want to build reliable GenAI systems.
What you will achieve
Engineer LLM applications; build and evaluate RAG systems; design agentic workflows; integrate tools and APIs; manage safety, privacy, latency and cost; deploy an enterprise GenAI capstone.
Prerequisites
Python proficiency and comfort with APIs are recommended. Prior machine learning experience is useful but not mandatory.
Learn. Apply. Build.
Each module builds toward a practical final project. Contents may be refined before your cohort begins.
Capstone project
Design, build, evaluate and present a production-oriented enterprise GenAI application or agentic workflow with security, governance, cost and adoption considerations.
Tokens, context, model selection, structured outputs, application patterns and failure modes
Prompt systems, test sets, automated evaluation, human review and quality measurement
APIs, streaming, structured data, tool calling, caching, reliability and cost controls
Chunking, embeddings, retrieval, reranking, grounding, permissions and citation patterns
Text, image and document workflows, extraction, classification and multimodal reasoning patterns
Planning, tools, memory patterns, multi-step workflows, guardrails and human-in-the-loop design
Prompt injection, data leakage, access control, red teaming, governance and risk controls
Observability, evaluation pipelines, latency, cost, versioning, incident response and vendor strategy
Mentor-led build sprints culminating in a production-oriented GenAI or agentic system
Invest in your next career step.
Create or verify your account, select this program, and receive a secure checkout link by email.