Training activity information
Details
Clean and prepare a healthcare dataset for an AI study and make recommendations for appropriate AI algorithms by undertaking Exploratory Data Analysis (EDA)
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
- Characterisation of the problem and/or question to be solved
- Existing methods and gold standards
- Legislation
- Feature engineering and selection
- Missing data and outliers
- Statistical methods for representing and summarising datasets
- Dimensionality reduction
- Classification vs regression
- Supervised vs unsupervised machine learning
- Appropriate algorithms
- Processing appropriate to data type
- Best practice, sharing knowledge and output
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 10 |
Outcome
Design, develop, train and validate AI models using alphanumeric and imaging datasets. |