A1 Computer fundamentals
A2 Networks
A3 Databases
A4 Machine learning
A4.1 Machine learning fundamentals
A4.2 Data preprocessing (HL only)
A4.3 Machine learning approaches (HL only)
A4.4 Ethical considerations
B1 Computational thinking
B2 Programming
B3 Object-oriented programming
B4 Abstract data types (HL only)
A4.3.1 Linear Regression in Predicting Continuous Outcomes (HL only)
A4.3.2 Classification Techniques in Supervised Learning (HL only)
A4.3.3 Role of Hyperparameter Tuning in Supervised Learning Algorithms (HL only)
A4.3.4 Clustering Techniques in Unsupervised Learning (HL only)
A4.3.5 Learning Techniques Using the Association Rule Used in Large Data Sets (HL only)
A4.3.6 Agents Learning to Make Decisions (HL only)
A4.3.7 Application of Genetic Algorithms (HL only)
A4.3.8 Structure and Function of ANNs (HL only)
A4.3.9 Design of CNNs (HL only)
A4.3.10 Model Selection and Comparison in Machine Learning (HL only)