Table 3 Learning elements selected for exclusion, organized by core theme and round in which consensus was achieved

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

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