ENGSCI 233 : Computational Techniques and Computer Systems

Engineering

2025 Semester One (1253) (15 POINTS)

Course Prescription

Introduction to computer architecture and computational techniques. Data representation, memory, hardware, interfacing, and limitations. Numerical computation and algorithms, coding design and paradigms.

Course Overview

This course will familiarise you with several coding areas that are important for computer modelling. This includes understanding the limitations of how computations are performed on hardware (memory, bandwidth, floating point error); key algorithms in linear algebra, calculus, and ODEs; and modern software development practices like version control, parallelisation and code optimisation. The course will have you using the Python program language and MicroBit computers.

Course Requirements

Prerequisite: ELECTENG 101 and ENGGEN 131, and ENGGEN 150 or ENGSCI 111 Corequisite: ENGSCI 211 or 213

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 6: Communication

Learning Outcomes

By the end of this course, students will be able to:
  1. Implement algorithms for data management (file I/O, directory management, file movement) and data structure concepts (Linked Lists, Networks). (Capability 3.1 and 3.2)
  2. Implement algorithms for searching, sorting and network concepts (e.g., breadth vs. depth search, insertion vs heap sort, Dijkstra's algorithm). (Capability 3.1 and 3.2)
  3. Implement algorithms for floating point error quantification (representation, rounding, division) and apply these in context (e.g. an LU factorization implementation). Implement a convergence algorithm. (Capability 3.1 and 3.2)
  4. Implement algorithms for numerical interpolation (polynomial fitting, linear interpolation, cubic splines) and integration (Newton-Cotes methods, Gaussian quadrature) and apply these to discrete data. (Capability 3.1 and 3.2)
  5. Implement algorithms to solve ordinary differential equations and quantify their properties (order, accuracy, convergence and stability). (Capability 3.1 and 3.2)
  6. Use profiling tools to identify and optimise bottlenecks in code. Apply Big O notation to understand algorithm scaling. Apply concepts of parallelisation to batches of independent tasks. (Capability 3.1 and 4.2)
  7. Understand binary integer representation and how this applies to floating point, ASCII, and structs. (Capability 3.1)
  8. Understand concepts of data transfer, data storage (memory), parallel vs. serial communication. Demonstrate how executing code can expose hardware limitations in the form of timeouts or out-of-memory errors. (Capability 3.1)
  9. Apply concepts of software quality control, including writing function specifications, use of error handling, development of unit tests, and use of a simple code repository for version control. (Capability 3.1 and 3.2)
  10. Interpret and communicate the results of applying computational techniques to various engineering problems. (Capability 4.1 and 6.1)

Assessments

Assessment Type Percentage Classification
Assignments 60% Individual Coursework
Test 10% Individual Test
Final Exam 30% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7 8 9 10
Assignments
Test
Final Exam

A passing mark is 50% or higher, according to University policy.

This course uses Exam mode C - In-person invigilated exam on paper. Students must sit the exam to pass the course. Otherwise, a DNS (did not sit) result will be returned.

Late assignments are penalised at 4% of the total mark per hour (or part thereof).  For example, if an assignment is marked out of 50, and submitted 130 minutes late, then 4+4+4= 12% of 50 (i.e. 6 marks) would be deducted from your total.

Teaching & Learning Methods

Concepts are explained during lectures (typically 2 per week), while practical coding skills are developed during the weekly 2-hour long lab sessions.  It is particularly important to attend the lab sessions, where students work through assignment material with the lecturer and Teaching Assistants on hand to help.  The fortnightly assignments are a key component of the course with each of the 6 assignments being worth 10% of the final grade, so it is important to fully engage with them.

While lectures are recorded, we strongly encourage students to attend in person to maximise their learning opportunities.    

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For each week in this course, you can expect 2-3 hours of lectures, a 2 hour computer lab, and 5-6 hours of work on assignments and/or test preparation.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities, including labs, to complete course components.
Lectures will be available as recordings. Other learning activities, including labs, will not be available as recordings.

Attendance on campus is required for the test and final exam.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

There is no required course book or text book for this course. Rather, learning materials will be made available electronically through Canvas.

Health & Safety

Students must ensure they are familiar with their Health and Safety responsibilities, as described in the university's Health and Safety policy.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Several improvements will be made to the course in response to issues identified by the 2024 student cohort.

Having only one of the weekly lectures occur before the weekly lab streams was a problem and did not allow as much theory to be covered before the labs took place.  For 2025, both lectures have been timetabled to occur before the lab streams.

Some students found it challenging to pick up Python alongside learning course concepts.  Some additional resources and extra sessions will be provided in 2025 for those who want extra help learning to code in Python.

Students commented that some of the assignment briefs were open to interpretation and that the assignments were not marked promptly.  Assignment briefs will be made more explicit for 2025, alongside changes to the marking process to speed up the return of marked material.


Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework, tests and examinations as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. A student's assessed work may be reviewed against electronic source material using computerised detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerised review.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.