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Leadership

Know where your IT footprint actually sits, and which levers are yours to pull.

Nine modules on the estate a CIO signs for: devices, data centre, cloud, network, demand, procurement and disposal. Where the impact is created, what you control, how to run a reduction and prove it, and how to disclose it without overclaiming. Every module ends on the same three questions — what you decide, what you ask for, what you sign.
6h 50m
of learning
9
modules
120 question
final assessment
80%
to pass
Credential
on completion

Green IT for Leaders

What
How
Tools
Who

How the course works

Concepts first, standards second

Boundary, materiality, baselines, targets and management cycles are taught as ideas. The frameworks that formalise them are named once, in Module 8, and dated — so the rest of the course holds when a specification changes.

Written for four audiences at once

Every module closes on what you decide, what you ask for and what you sign, with a short note wherever a CIO, a CFO, a sustainability lead and a public-sector buyer would genuinely decide differently.

Two exercise modes

An in-course Northbridge decision you can finish immediately with the figures supplied, and the same exercise to repeat at work when you have your own.

What this course helps with

A third of the footprint is on no bill

Manufacturing impact is incurred before a device is switched on and never appears on an energy invoice. In the worked estate it is 36% of the total — so an organisation measuring electricity is measuring about two thirds and calling it the whole.

The biggest levers are signatures, not projects

A refresh policy, a disposal contract, an RFP clause. In the worked estate, one extra year of device life is worth about 1,160 tCO₂e a year and costs nothing to decide.

Claims that do not survive review

Carbon that fell while energy did not. A rate reported without a total. A boundary that quietly excludes the largest component. Module 8 covers how each is caught.

Who this is for

  • CIOs, CTOs and IT directors accountable for the estate and its suppliers

  • CFOs, COOs and board members funding IT and answering for what is disclosed

  • Public-sector IT leadership working within procurement rules

  • Sustainability leads who need IT to produce figures that survive assurance

  • No technical background and no prior course assumed

Related courses:

This course covers the estate and leaves workload depth to the practitioner track. For AI specifically, see Green AI for Executives. For starting and scaling a programme, see Getting Started and Scaling Green Software and Green AI. For the data estate, see Green Data Practitioner.

What you will work with

The estate map

A first-pass footprint built in a day from four sources you already have — asset register, cloud invoices, energy bills, procurement records — with every figure marked estimate or measurement.

The refresh and disposal card

What one extra year of device life is worth, why the same policy can be wrong for servers, and the five things a disposal contract must guarantee.

The lever ranking and savings register

Impact against control and time to effect, one owner per tonne, and the guard that stops a saving decaying once attention moves on.

The claim checklist

Metric, boundary, method, basis, date and quality — plus the four ways an IT sustainability claim typically fails, and the single question that exposes the most common one.

What you will be able to do

  • Define Green IT, and say which of carbon, energy, water and waste your organisation actually measures
  • Tell a total estate footprint from a software footprint, and say which question each answers
  • Decide a boundary, and justify what you excluded from it
  • Separate an efficiency improvement from a carbon-intensity change, and report each as what it is
  • Evaluate a refresh cycle on carbon as well as cost, and say where extending life is the wrong answer
  • Interrogate a provider’s PUE, WUE and utilisation claims, and read a refusal as an answer
  • Rank levers on impact, cost, control, risk and time — then quantify one saving and guard it
  • Judge whether a figure in front of you would survive assurance

Course Lessons

The full course

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

01

Where ML’s Footprint Is Decided

A model’s footprint is created twice: once when it is trained, and again on every inference it serves. This module sets the decision metric and the amortisation rule that every later module is judged against.
module-01

02

Reuse, Adapt, or Train: The First Decision

The largest reduction available on the training side is not to train, yet the question is usually settled by habit before anyone computes it. This module compares six routes to a working model and what to ask of a base model before inheriting its cost.
module-02

03

Sizing the Model and the Data Budget

How large a model, trained on how much data, sets the energy term more directly than any later choice. This module covers compute-optimal sizing and how architecture changes training and serving energy independently of parameter count.
module-03

04

Data Efficiency: What the Model Is Trained On

What the training tokens actually are changes both how many are needed and how good the resulting model is. This is the layer where the footprint lever and the quality lever most often point in the same direction, and this module is careful about where that alignment breaks.
module-04

05

The Training Run: Execution, Stopping and Waste

This module examines the compute that produces nothing: epochs past convergence, crashes without a checkpoint, and experiments that repeat work already done. Waste at this layer is invisible in a cost report, because a failed run and a successful one look identical on the bill.
module-05

06

Search and Evaluation: The Two Multipliers

Earlier modules reduce the cost of one run; this one addresses how many runs happen, which is usually the larger number. It covers search budgets, comparing strategies by cost per answer, and evaluation as a cost that recurs for the life of the model.
module-06

07

Hardware-Aware Training

Compute demanded is one quantity; how efficiently it becomes energy is another. This module covers precision, batch size, accelerator fit and utilisation as the conversion factor sitting between the two.
module-07

08

When and Where to Train

This is the one lever that changes carbon without changing energy, by moving a run to a different hour or region. Training is often a strong candidate, and this module covers the constraints that decide it, along with water, preemptible capacity and embodied allocation.
module-08

09

From Weights to Deployable Artifact

This module deliberately spends training cost once in order to reduce serving cost on every inference that follows. It covers parameter-efficient adaptation, post-training and compression, and the repayment calculation that decides whether the trade is worth making.
module-09

10

Lifecycle, Retirement and Disclosure

Retraining cadence multiplies the training footprint, and retirement is the point at which every amortisation estimate becomes a measured fact. This closing module covers cadence, drift, registry and model card records, disclosure duties, and the capstone footprint report.
module-10

11

Final Assessment

A final assessment of 30 scenario-judgement questions - 80% to pass, 60 minutes, retake available.

Assessment and Credential

How you are assessed

  • A five-question knowledge check after every module, drawn at random from that module’s ten-question pool
  • A final assessment of 20 questions drawn from a pool of 86, covering all nine modules
  • 80% to pass, 30 minutes, retake available after 30 days
  • Drawn from a bank of 181 questions — every one tests a leadership decision rather than recall of a figure that dates

What you earn

GSF Certified
Green IT Leader
  • Issued on passing the final assessment
  • Valid for three years, refreshed by a short update module
  • Shareable credential for your profile, CV and tender responses

Time to complete

Reading and exercises
6h 50m across 9 modules
Knowledge checks
About 5 minutes per module
Final assessment
30 minutes
Typical completion
 2–3 weeks at a module per session, entirely self-paced
Apply at work
 Additional, and paced by how quickly suppliers and colleagues respond

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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