Every certification publishes what it measures — the knowledge domains, how heavily each is weighted, the difficulty split, the duration and the pass mark — before you sit it.
AI Application Engineering & Agentic Systems
Certifies judgement in deploying and owning systems inside customer environments.
3 levels · from $99
ML / AI Systems & Modeling
Designs the measurement: what counts as correct, how it is judged, and why the benchmark can be trusted.
Security, Safety & Governance
Makes AI use defensible: inventory, risk classification, documented controls and evidence a regulator would accept.
AI Infrastructure, Platforms & Operations
Designs and operates the infrastructure AI workloads run on, from accelerator choice to inference topology.
AI Infrastructure, Platforms & Operations
Finds where the time and the money actually go, and proves the optimisation worked.
Architecture, Product & Leadership
Decides what an AI product should do, what quality bar it must clear, and what it must refuse to do.
AI Infrastructure, Platforms & Operations
Defines what 'working' means for a non-deterministic system, measures it, and runs the incident when it stops.
ML / AI Systems & Modeling
Builds the systems research runs on: training infrastructure, reproducibility, scaling and experiment tooling.
Security, Safety & Governance
Works on the harms a correctly functioning system can still cause, and on the controls that reduce them.
Security, Safety & Governance
Models the attack surface of AI systems and chooses mitigations that survive contact with a real adversary.
Architecture, Product & Leadership
Architects AI-bearing systems: where the model sits, what it is allowed to do, and what happens when it is wrong.
AI Application Engineering & Agentic Systems
Designs multi-step agent systems: tool use, planning, state, recovery and the limits of autonomy.
Data Engineering & Modern Data Stack
Turns raw tables into a modelled, tested, documented layer the business can query without asking anyone.
AI Application Engineering & Agentic Systems
Applies existing models to concrete business problems end to end, choosing when not to use a model at all.
ML / AI Systems & Modeling
Turns an open research question into a measurable, shippable result, and knows when the result does not hold.
AI Infrastructure, Platforms & Operations
Delivers AI workloads on managed cloud services, and owns the identity, network and cost consequences.
ML / AI Systems & Modeling
Builds systems that interpret images and video, and knows how they fail on data the camera actually produces.
Data Engineering & Modern Data Stack
Decides how an organisation's data is shaped, owned, governed and allowed to move.
Data Engineering & Modern Data Stack
Moves data reliably and makes it trustworthy at the point of use.
Data Engineering & Modern Data Stack
Operates the shared data platform: ingestion, compute, catalogue, access and the cost of all of it.
Data Engineering & Modern Data Stack
Answers a business question with data honestly, including when the data cannot answer it.
Architecture, Product & Leadership
Works at the level of capabilities, standards and multi-year sequencing rather than individual systems.
AI Infrastructure, Platforms & Operations
Runs the compute, storage and network layer that training and inference actually consume.
AI Infrastructure, Platforms & Operations
Builds the internal platform other ML teams build on, and is judged on their throughput rather than their code.
AI Infrastructure, Platforms & Operations
Owns the path from a trained model to a served one, and everything that keeps it serving correctly.
ML / AI Systems & Modeling
Builds, trains, validates and ships models, and owns their behaviour once real data reaches them.
ML / AI Systems & Modeling
Works on language tasks end to end, including the many that should not be solved with a large model.
Architecture, Product & Leadership
Owns the structure of a system: its boundaries, its failure behaviour, and the decisions that are expensive to reverse.
Architecture, Product & Leadership
Designs a solution against real constraints and defends the trade-off to the people who have to live with it.
Architecture, Product & Leadership
Is accountable for a team's technical output: sequencing, quality, review, and the decisions nobody else will make.
AI Application Engineering & Agentic Systems
Validates the ability to design, ground, evaluate and operate an application built on a language model.
AI Application Engineering & Agentic Systems
Selects, adapts, serves and evaluates language models, and reasons about behaviour that changes between identical calls.
