Emerging Skills Program — no certification exam
Digital Asset Integrity & Predictive Analytics
Turning inspection, condition and process data into integrity decisions — and recognising, early, when the data will not support the claim being made for it.
Why this matters
The problem this solves
Most digital integrity programmes fail on the data, not the analytics — and they usually fail quietly, producing dashboards that are wrong rather than dashboards that are empty.
Corrosion rates from thickness histories with unrecorded probe positions. Condition indices built on a sensor set installed for process control. Remaining-life predictions from four data points across nine years. The mathematics is rarely the problem; the problem is that the underlying data was never collected to answer the question being asked of it.
This programme is about assessing that honestly. What the data can support, what a condition-monitoring architecture has to look like under ISO 13374, where a digital twin genuinely earns its keep, and how to evaluate a vendor claim without needing to be a data scientist.
Before you enrol
Is this a certification?
The short answer is no, and it is worth being explicit about it rather than leaving it to be discovered later.
What this programme gives you
- Three days on data quality, condition monitoring architecture and honest prediction
- Worked corrosion-rate analysis from real repeat thickness data
- A vendor evaluation question set you can use in a procurement
- An EIM certificate of completion
What it does not
- Not preparation for a certification exam — no certifying body examines this subject
- Not a data science or machine learning engineering qualification
- Not a vendor platform certification
- Not a substitute for the inspection that generates the data in the first place
If you need a recognised credential, start at certification exam preparation.
Who it's for
Roles this is built around
Asset integrity engineers
Any level
Being asked to move a programme onto a platform, and needing to know what will actually transfer.
Reliability and condition monitoring engineers
Technical
Holding the sensor data everybody now wants predictions from.
Integrity and digital programme managers
Decision level
Evaluating vendor claims and having to justify the spend afterwards.
What it covers
The outline
An outline, not a weighted Body of Knowledge — nobody publishes weights for a subject with no exam behind it.
What the data has to be
Provenance, position, calibration and continuity — the four things that decide whether analysis is possible.
Thickness histories, honestly
Corrosion rates from repeat UT, and the measurement uncertainty most rate calculations quietly ignore.
Condition monitoring architecture
ISO 13374 and ISO 17359 — from data acquisition to a decision, and what belongs at each layer.
Prediction and its limits
What condition and process data genuinely support, and the sample sizes real integrity datasets have.
Digital twins in integrity
Where a model earns its keep, where it becomes an expensive drawing, and the maintenance burden either way.
Evaluating a claim
Questions that separate a working system from a demonstration, without needing to be a data scientist.
Outcomes
What you will be able to do
- Judge whether an existing dataset can support the integrity question being asked of it
- Calculate corrosion rates from repeat thickness data with a defensible treatment of uncertainty
- Design a condition monitoring architecture along ISO 13374 layers
- Distinguish a genuine predictive capability from a trend line with a confident label
- Decide where a digital twin is worth the maintenance it will demand
- Interrogate a vendor claim well enough to know what you would be buying
Standards referenced
What the programme works from
| Standard | What we use it for | Note |
|---|---|---|
| ISO 13374 | Condition monitoring and diagnostics — data processing and presentation | The architecture reference |
| ISO 17359 | Condition monitoring and diagnostics — general guidelines | — |
| ISO 55001 | Asset management — management systems | The governing frame |
| API RP 584 | Integrity Operating Windows | The most common real-time integrity use case |
How it runs
Ways to take it
Formats offered — not scheduled dates. Live cohort dates live on the course page, so there is only ever one copy of a date.
| Format | Duration | Group size | Notes |
|---|---|---|---|
| Live online | 3 days | Up to 15 | Split across sessions rather than run as consecutive full days |
| In-house | By arrangement | 6–20 | Delivered against your own equipment, your own findings and your own procedures |
FAQs
Questions people ask first
No. The programme is aimed at integrity and reliability engineers, and its purpose is to make you a competent judge of what data and analytics can deliver — not to turn you into a data scientist.
No. The AI programme is about language models in day-to-day engineering work — reports, documentation, standard lookup. This one is about instrument, inspection and process data, and the integrity decisions built on top of it.
No, and deliberately. It gives you the questions to ask of any platform, which outlasts any particular recommendation and does not put us in the position of selling somebody else’s software.
Want the full outline?
Tell us your role and what you are trying to fix, and we will send the programme outline and what it would take to run it for your team.