The HL Computer Science course builds on the SL foundation, providing deeper study in computational thinking and . Students explore all SL topics with expanded breadth and depth, plus HL-only material in programming, object-oriented programming, and data types. Key topics include CPU/GPU differences, pipelining, multitasking, and control systems, alongside the TCP/IP model and server functions in networking.

In the field of databases, students will learn about advanced SQL and transactions, alternative databases, and data mining techniques. Machine learning topics such as preprocessing, regression, and classification are also covered, along with ethical considerations associated with these technologies. Programming content focuses on recursive algorithms and advanced problem-solving strategies.

The course also emphasizes object-oriented programming, covering multiple classes, inheritance, and design patterns. Additionally, HL-only content includes abstract data types like linked lists, BSTs, and hash tables, emphasizing their applications in various scenarios.

Assessment in the course consists of Paper 1 and Paper 2, each with a duration of hours, accounting for 40% of the final grade, and an internal assessment that takes 35 hours and contributes 20% to the final assessment. Paper 1 comprises extended-response questions and short-answer questions, while Paper 2 focuses on computational thinking and problem-solving.