Develop systems that learn through experience and by the use of data.
Level 1 (Follow)
Level 2 (Assist)
Level 3 (Apply)
- Apply existing machine learning techniques to new problems and datasets.
- Evaluate the outcomes and performance of machine learning systems.
- Identify issues and recommend improvements to machine learning systems and the data they use.
Level 4 (Ensure)
- Given a well-described problem and dataset, assess whether machine learning is likely to provide an effective solution.
- Implement algorithms developed by others.
- Advise on the effectiveness of specific techniques, based on project findings and wider research.
- Contribute to the development, evaluation, monitoring and deployment of machine learning systems.
- Understand and apply rules and guidelines specific to the industry, and anticipate risks and other implications of modelling.
- Design, implement, test and improve machine learning architectures and systems.
- Select techniques based on a breadth of knowledge of the strengths, weaknesses and expected performance of different approaches.
- Establish good practice in the development, evaluation, monitoring and deployment of machine learning systems.
Level 5 (Strategise)
- Lead the development of new approaches and organisational capabilities to design, train, and evaluate machine learning systems.
- Set standards and guidelines for the application and traceability of machine learning systems to business problems, and oversees their implementation.
- Design and oversee organisational policies on the creation, training and use of machine learning systems.