Table 3.

Learning elements selected for exclusion, organized by core theme and round in which consensus was achieved

Theme	Element for exclusion	Consensus round
Theory
T29	Explain the basic structure and function of a computer, including the central processing unit, memory, and storage.	2
T30	Identify the different types of hardware components and their roles in computer operation.	2
T31	Evaluate the impact of hardware specifications on computer performance and application capabilities.	2
T32	Understand the fundamental concepts of programming, including data types, control structures, functions, and algorithms.	2
Application
A12	Apply programming concepts to build AI models, tools, and simple healthcare applications.	2
A13	Define gradient descent in machine learning models.	2
A14	Implement regularization techniques to reduce overfitting in models.	2
A15	Understand and apply backpropagation for deep learning models.	2
A16	Use kernels to transform data in machine learning and deep learning models.	2
A17	Understand and apply clustering techniques for unsupervised learning.	3
A18	Implement anomaly detection techniques for identifying outliers in data.	2
A19	Apply vectorization techniques to optimize code in machine learning and deep learning models using Python.	2
A20	Use TensorFlow to build and train deep learning models.	2