Enrolment
This course is currently free to enrol in.
Public course
Enterprise AI — Course 2: Understanding Model Behaviour
This course develops evidence-based diagnosis of AI results, recognition of user influence, and targeted checks using sources, context and processing records.
enterprise AImodel behaviourcontextuser biasverificationstructured outputdiagnosis
By Telari Labs
Learning on Telari
Created by Telari Labs, delivered through Telari
The course creator controls the material and assessment standards. Telari provides structured lessons, practice, feedback against those standards and a record of your progress. See how Telari works.
AI access
The first managed lesson is included on Free. Continue with Plus or your own supported API key; premium assessments and certificates may require Plus.
Audio
No reviewed lesson audio is currently advertised for this course.
Lesson list
- Learned behaviour and supplied evidenceThis lesson separates learned capability, information supplied for a request and evidence that supports a particular answer.
- Context and information availabilityThis lesson follows information from its source into the actual model input and identifies what an omission or misleading summary can explain.
- Instructions, examples and conflicting contentThis lesson distinguishes unclear task definitions from source content and action permissions, using precise clarifications and bounded checks.
- Output structure and meaningThis lesson separates parsing, schema checks, source fidelity and business rules, including correct treatment of unknown values.
- Framing, variation and confidenceThis lesson examines how user framing and prior assumptions interact with agreement, confidence and variation, and develops proportionate evidence checks.
- Locating failures across stagesThis lesson uses compact intermediate records to locate a justified next investigation and distinguish an action request from a confirmed result.
- Diagnosing an unfamiliar resultThis assessment combines source checking, context, user influence and staged diagnosis in new cases.