Computing

Elective Unit

Prerequisites

There are no prerequisites for this course.

Course Description

This full-year Computing elective builds on the foundational concepts introduced in Year 9 and explores a broad range of technology skills. The course is designed to build a strong foundation for further study in computing, while also developing analytical and problem-solving skills that are increasingly valuable across science, engineering, business, medicine, design and many other fields.

Students deepen their understanding of data management, working with relational databases and SQLite to design, query and manipulate structured data, and extend this into data analytics, learning to clean, explore and interpret real-world datasets to uncover patterns and draw evidence-based conclusions. Students are introduced to artificial intelligence and machine learning using Python and the scikit-learn library, applying concepts such as classification, regression and model evaluation to build and test their own predictive models. The course also strengthens students' understanding of algorithm design and coding (using Python), and their awareness of cybersecurity, including how data is protected as it moves across networks.

Areas of Study

Databases
Organising data and database management systems, including relational database design and querying using SQL/SQLite.

Data Analytics
Cleaning, exploring and visualising datasets to identify trends and outliers, and communicate findings using evidence-based reasoning.

Artificial Intelligence and Machine Learning
Introducing machine learning concepts through Python and scikit-learn, including training, testing and evaluating classification and regression models.

Cybersecurity and Networks
Understanding how data is transmitted and protected online, including core encryption principles.

Algorithms
Expressing algorithmic thinking using pseudocode, and comparing algorithmic approaches such as searching, sorting, brute-force and recursive strategies in terms of correctness and efficiency.

Coding a Software Solution
Coding fundamentals, accessing files and building graphical user interfaces, extending into object-oriented programming to design and structure more advanced software solutions.

Assessment

Task	Description
Develop a Database Solution	Students design and build a database solution to meet the requirements of a provided scenario.
Design an Algorithmic Solution	Students design and compare algorithmic approaches, using pseudocode, to solve a nominated problem.
Data Analytics and Machine Learning Investigation	Students analyse a real-world dataset and apply a machine learning model using Python and scikit-learn to make predictions or classifications, evaluating the model's performance and limitations.
Coding a Software Solution to a Real-World Problem	Students build a software solution using the skills related to the specific modules which they studied.
Examination	Students undertake an examination at the conclusion of the course.