COMP6730
Programming for Scientists
- Credit
- 6 units
- Catalogue year
- 2027
- Recorded offerings
- First Semester, Second Semester
Course information
This course teaches introductory programming, fundamental programming language and computer science concepts, and computational problem solving illustrated with applications common in science and engineering, such as data analysis, visualisation, and image processing. We will take a different approach, including prompting and working with GenAI, with emphasis on testing, debugging and problem decomposition, and using GenAI to help understand code.These skills will empower students to write software with the aid of GenAI. Assessment will include exam(s) without the aid of GenAI. Students will also create larger software projects with the aid of GenAI. The course does not require any prior knowledge of programming or computer science. It is designed to be a stand-alone computing unit.Students who wish to study computing courses at a higher level should check course prerequisites as they may need to complete COMP6710 or COMP7710 in addition to COMP6730.
Requisite and Incompatibility
You are not able to enrol in this course if you have successfully completed COMP1100, COMP1130, COMP1730, COMP6710 or COMP7710.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Apply advanced programming constructs and structured programming methodologies to develop reliable software systems.
Explain key concepts in AI-assisted programming, including Large Language Models (LLMs), prompting, problem decomposition, and top-down design.
Apply AI-assisted programming workflows and advanced prompt-engineering techniques to guide, refine, and improve code generated by AI assistants.
Analyse the computational complexity of programs, and apply debugging and testing techniques, including black-box and white-box testing.
Evaluate and improve code quality using critical judgement.
Design and implement complete programs that solve practical problems using structured programming methodologies and AI-assisted prompting.
Critically evaluate the role, benefits, limitations, and risks of generative AI in software development projects
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