Write your awesome label here.
Design a data estate against carbon, energy, water and waste, from sourcing through to disposal.
Thirteen modules following the data lifecycle: source, model, store, process, place, serve, index, retain, dispose and telemetry, each measured against SCI, and each ending in the design gate that stage cannot be signed off without.
10h 40m
13
30 questions
80%
Certification
Green Data Practitioner
How the course works
One lifecycle, one expression
SCI runs through all thirteen modules, with E split into stored, moved and scanned, I as the carbon-aware term, M as media and servers, and R as the functional unit you choose.
A design gate at every stage
Each of Modules 3 to 11 ends with the question to require before sign-off, and Module 12 assembles the nine into a review artefact.
Patterns with the trade stated
Around fifty catalog entries, each naming the term it moves and whether it saves once or on every hour, query or run.
What this course helps with
See where a data estate actually costs
Stored, moved and scanned bytes run on three different clocks, and the mechanism that dominates a service is frequently not the one it is named after.
Design it in rather than remediate it
Almost every expensive data decision is cheap when it is taken and paid at a later stage — the course puts the question before the decision.
Cover what the estate-level courses leave short
Warehouse layout, index and vector economics, retention authority and telemetry get a module each rather than a section.
Who this is for
- Data engineers and analytics engineers
- Database, warehouse and platform engineers
- Data architects and technical leads responsible for a data estate
- ML and AI engineers who own retrieval, feature or vector stores
- Assumes working familiarity with data systems; no sustainability background required
Related courses:
For estate-wide architecture across six layers, see Green and Efficient Architect; for training-side model decisions, see Green AI for ML Practitioners; for producing the underlying figures, see SCI for AI Practitioner.
What you will work with
The three mechanisms
Why a small hot table can cost more than a large cold archive, and which lever works on each.
The copy count
One 1.2 TB warehouse, nine physical copies, and the policies that created them separately.
The Green Data Blueprint
Four blocks (assessment, measurement plan, pattern register and governance wiring) bound by a traceability test.
What you will be able to do
Course Lessons
The full course
01
The Prompt Footprint
Introduces the five-dimensional view: cost, carbon, energy, water, embodied hardware. Establishes SCI for AI as the standards anchor. Positions the regulatory landscape (CSRD, EU AI Act, procurement disclosure) as the why now for Footprint literacy.
Before You Begin
Modules
02
The Specification Lever
How prompt intent quality drives Footprint. The GSF Intent Framework introduced. Trade-offs: over-specification wastes tokens, under-specification wastes retries. Worked examples across capability tiers.
Modules
03
The Structure Lever
Prompt organization: system messages, few-shot examples, output constraints, formatting instructions. Where structure earns its tokens and where it doesn't.
Modules
04
The Reasoning Depth Lever
When to invoke chain-of-thought, tree-of-thought, extended reasoning modes; when not to. The GSF Reasoning Budget: task-class taxonomy for reasoning depth decisions.
Modules
05
The Model Selection Lever
The most consequential single decision in inference efficiency. Capability tiers and routing decisions. The GSF Model Fit Test protocol. Same task across tiers, measured.
Halfway Check-in
Modules
06
The Orchestration Lever
Where agents leak resource: tool selection, chain depth, redundant retrieval, missing caching. Token budgets as a first-class design constraint. Case study from the supply-chain agent paper (70–90% workflow-level savings).
Modules
07
Measuring the Prompt Footprint
Hands-on demonstrations with EcoLogits, CodeCarbon, AI Energy Score. Producing numbers a CSRD auditor can read. The measurement chain from token count to gCO₂eq.
Modules
08
Procurement & Disclosure
What to ask your LLM vendor. What CSRD and the EU AI Act will require. The GSF Procurement question bank organized by Footprint dimension.
Modules
09
Course Completion
50 questions, 120 minutes. Pass Marks: 85%
Final Assessment
Share Your Feedback
Assessment & Certification
Time to complete