Training activity information
Details
Validate and interpret the output of an AI model and present findings to an audience of peers
Type
Developmental training activity (DTA)
Evidence requirements
Evidence the activity has been undertaken by the trainee.
Reflection on the activity at one or more time points after the event including learning from the activity and/or areas of the trainees practice for development.
An action plan to implement learning and/or to address skills or knowledge gaps identified.
Considerations
- Underlying algorithms
- Requirements for test data
- Statistical modelling
- Documentation
- Commercial systems
- Use and interpretation of performance metrics
- Validation techniques, including k-fold cross-validation
- Bias – variance tradeoff, learning curves
- ‘Acceptable’ false positive and false negative rates
- Best practice, sharing knowledge and output reproducibility
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 10 |
Outcome
Design, develop, train and validate AI models using alphanumeric and imaging datasets. |