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Leadership

Start a green software and green AI program, and grow it beyond the first team.

An adoption journey in seven steps: map the footprint, build awareness and choose a first portfolio, set a baseline, apply patterns, embed checks in delivery, run reduction campaigns, and keep it going with a dashboard and a governance rhythm.
5h 15m
of learning
7
modules
30 question
final assessment
80%
to pass
Certification
on completion

Scaling Green AI and Software

What
How
Tools
Who

How the course works

One organization throughout

Northbridge appears in every module, with the same estate and the same numbers, so the steps connect into a single journey.

Patterns from a curated catalog

Each reduction has a precondition, a trade-off and a verification step, and is applied through a select–apply–verify loop.

A workbook you fill in

Seven steps that assemble into an adoption plan for your own organisation, each with a worked solution to check against.

What this course helps with

Awareness that holds

Understand the four dimensions (carbon, energy, water and waste) and where they're created across the estate, so the conversation starts from facts.

A first step that is small enough to take

A portfolio of a few workloads chosen on materiality, tractability and evidence, rather than a programme that tries to cover everything.

Work that continues after the launch

A cadence, an owner and a dashboard, so the program does not depend on one person’s attention — with reduction campaigns that cut consumption, and usually the bill for it, in the same pass.

Who this is for

  • Anyone starting or scaling a green program, in any role

  • Product, design, engineering, ML and data, platform and infrastructure teams

  • Procurement and governance colleagues joining the effort

  • No sustainability background required; Modules 3–6 assume familiarity with delivery tooling

Related courses:

Already measuring confidently and want depth on one layer? The practitioner courses go further on measurement, architecture and operations.

What you will work with

The portfolio test

Three questions (material, tractable, evidenced) for choosing the first workloads, and what to say to teams not in the first cohort.

A completed baseline row

Unit of work, rate and total, boundary, data tier and date, filled in for one service.

The campaign design

Scope, baseline, quality bar and the go/no-go stated before the work begins.

What you will be able to do

  • Explain green software's four dimensions (carbon, energy, water and waste) and where each arises across your estate
  • Build awareness across every role, and choose a first portfolio
  • Produce a baseline for that portfolio, with the unit of work, boundary and data quality stated for each figure
  • Apply patterns and run reduction campaigns, and verify each result with a before-and-after measurement
  • Add green checks to your delivery pipelines for software, machine learning (ML) and AI agents
  • Set up a minimum viable dashboard and a governance rhythm, and write a 90-day plan to scale beyond the first portfolio

Course Lessons

The full course

Every module ends with an application exercise and a worked solution.

01

Why Water, and Why You

Software feels dry, but the buildings it runs in use water for cooling, the electricity it consumes was made using water, and the hardware was manufactured with it. This module shows those three connections and closes the gap between the people who can see the water and the people who change the software.
module-01

02

The Four Layers: building, electricity, hardware, and the stress conversion

This module gives the three ways software uses water their proper names, as the draft SWI specification uses them, and adds a fourth layer that converts litres into how much each litre matters. It ends with the only line of arithmetic in the course.
module-02

03

Consumption and Withdrawal: used up vs borrowed

Water figures come in two kinds, and confusing them is the most common mistake in reading them. This module teaches the distinction between water used up and water borrowed and returned, and the rule that the two are never added together.
module-03

04

Reading a Water Number

This module teaches no calculations. It teaches how to look at any water figure, whether a provider report, a news headline or a colleague’s slide, and know what it does and does not say.
module-04

05

Stress-Adjusted Water: a liter is not a liter

The same liter counts for more where water is scarce and for less where it is plentiful. This module turns that idea into arithmetic using a published factor per place, giving the conversion layer its full treatment at foundation depth.
module-05

06

Small Things That Save Water

The earlier modules built a vocabulary; this one turns it into actions small enough to take this week, organised by role. None of them needs a water meter, a budget or permission to run a project.
module-06

07

Final Assessment

A final assessment of 12 questions - 80% to pass, 30 minutes, retake available.
Final Assessment

Assessment & Certification

How you are assessed

  • A short knowledge check after every module, drawn at random from that module’s pool
  • A final assessment of 30 scenario-judgement questions from a pool of 105+
  • 80% to pass, 60 minutes, retake available
  • Questions test judgement in situations you will meet — not recall of figures that date

What you earn

GSF Certification
Green Software & AI Adoption Professional
  • Issued on passing the final assessment
  • Valid for 2 years, refreshed by a short update module
  • Shareable credential for your profile, CV and tender responses

Time to complete

Reading and exercises
5h 15m across 7 modules
Knowledge checks
About 5 minutes per module
Final assessment
60 minutes
Typical completion
1–2 weeks at a module per session, entirely self-paced

Join the Pilot

The GSF Academy is currently in pilot. If your organization would like to enrol learners and issue GSF certifications to your teams, tell us a little about what you need and we'll follow up to discuss access, pricing, and enrolment.

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