Course Catalogue

Programming for Engineers COMPSCI1033

  • Academic Session: 2026-27
  • School: School of Computing Science
  • Credits: 0
  • Level: Level 1 (SCQF level 7)
  • Typically Offered: Repeated in Semesters 1 and 2
  • Available to Visiting Students: Yes
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

This CPD course is designed to equip engineers with practical programming skills using Python, one of the most versatile and accessible programming languages widely adopted in the engineering industry. The course adopts a problem-solving approach with effective use of AI-assisted programming tools, covering real-world engineering scenarios and data-driven tasks such as automation, numerical computation, and simple data visualization. By the end of the course, learners will be able to write python scripts and small applications relevant to their engineering domain.

Timetable

Timetable will be planned by the local team in Singapore.

Requirements of Entry

■ Basic computer literacy

■ Engineering background (Diploma or equivalent and above)

■ No prior programming experience required

Excluded Courses

None

Co-requisites

None

Assessment

Quizzes: 20%, Practical Programming Test: 20%, Project: 30%, Final Exam/Test: 30%

Course Aims

To equip engineers with practical programming skills using Python, one of the most versatile and accessible programming languages widely adopted in the engineering industry. To provide learners with experience of real-world problem-solving using engineering scenarios and data-driven tasks such as automation, numerical computation, and simple data visualization. The course is suitable for working professional and engineers from disciplines such as electrical, mechanical, civil, and industrial engineering.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Understand core programming concepts including data types, control structures, functions, and error handling.

2. Apply Python programming to solve engineering problems and perform task automation.

3. Work with common libraries such as NumPy, Pandas, and Matplotlib for numerical and data tasks.

4. Develop small-scale software projects that reflect practical engineering use cases.

5. Demonstrate good programming practices including code structuring, testing, and documentation.

Minimum Requirement for Award of Credits

No exceptions