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Computer programming. Descriptive statistics. Monte Carlo and Bootstrapping methods. Design of experiments. Linear regression and generalized linear modelling. Optimization and linear programming.
● to improve students’ general programming skills, so they can develop solutions to engineering problems in Python and, potentially, in other programming languages.● to understand hypothesis testing and apply hypothesis test to different situations.● to introduce analytical approaches to examine dependence between different quantities for which observational data is available and use them for statistical inferences.● to understand basic concept of optimization methods and their applications in engineering.● to be able to solve numerically a range of optimization problems in engineering.
Students must attend one activity from each section.
This course is a lecture and lab-based course. There are 4 streams of labs/tutorials per week, you can view/select these via your timetable. Please note that you will have a single two hour lab per week in section 1 but, in sections 2 and 3, you will have two tutorials of two hours each week - see below for details.Section 1 - Computer Programming● The first lecture in week 1 is an introduction to the course – all students should attend.● All the other lectures in section 1 are provided through online videos.● Students are required to attend a two-hour computer lab each week.The aim of the computer lab will be to apply the knowledge that you have obtained from lectures and also with an opportunity to work on problems with the support of a tutor.Section 2 - Statistics (Weeks 7 to 10)● All the lectures in section 2 are provided through online videos.● Students are required to attend 2 computer-based tutorials each week covering different topics.Each tutorial will be provided in a computer room, in which you will use the programming technique learnt from section 1 to solve practical statistics problems. Tutorial topics will be release on Learn and you are expected to finish one topic in each tutorial. Both the lecturer and tutors will be in the tutorial.Note: In week 7, there will be no tutorials on the ANZAC day and there will be only one topic to be finished.Section 3 - Optimization (Weeks 11 & 12)● All the lectures in section 3 are provided through online videos.● Students are required to attend 2 computer-based tutorial each week.Each tutorial will be provided in a computer room, in which you will use the programming technique learnt from topic 1 to solve practical optimization problems. Tutorial topics will be release on Learn and you are expected to finish one topic each week. Both the lecturer and tutors will be in the tutorial.Expectation for all sectionsThe relevant material for lab exercises will be distributed ahead of the laboratory classes and tutorials. It is very important that you give these laboratory exercises some thought before attending the lab classes.Programming, statistics, and optimization are subjects that can only be learnt by doing. Unless you work consistently throughout the semester on associated problems and tutorials it is unlikely that you will be able to gain the skill level required to pass the course. Therefore we encourage you to allocate a significant amount of time each week to review the lecture material and work on relevant problems associated with the labs and tutorials.
and Andrew Bainbridge-Smith
You cannot pass this course unless you achieve a mark of at least 40% in each of the mid-semester test and the final exam. A student who narrowly fails to achieve 40% in either the test or exam, but who performs very well in the other, may be eligible for a pass in the course.A resit test may be held at the start of week 10 for students who do not achieve the 40% pass mark in the mid-semester test.Your attendance and work in each tutorial will be graded for assessment. If a student is unable to attend a tutorial of a topic due to personal circumstances beyond their control they should discuss this with the lecturer involved as soon as possible.Students may apply for special consideration if their performance in an assessment is affected by extenuating circumstances beyond their control, provided they have sat either the final exam, mid-semester test or both. Applications for special consideration should be submitted via the Examinations Office website http://www.canterbury.ac.nz/exams/ within 5 days of the assessment. However students must be aware of the following with regards to the programming half of the course:(a) Special Consideration cannot be sought for the individual moodle quizzes - we are happy to grant reasonable extensions, (b) we will NOT derive a grade for the mid-semester test, a student who misses the test will be offered a resit only.In the case of an emergency that affects the whole course, the Course Coordinator, in consultation with the Dean, may change the nature, weighting and timing of assessments, e.g. tests and examination may be replaced with assignments of the same weight or different weight at a different time and/or date (which, under certain circumstances, may be outside the prescribed course dates). The ‘Special consideration’ process will also be used for unforeseen circumstances that adversely affect the academic performance of students individually. The usual grounds for this are described in the UC policy ‘Special Consideration Procedures and Guidelines’, and personal circumstances due to a wider emergency event may also qualify".
All course materials will be made available through Learn and the CSSE quiz server.
Domestic fee $986.00
International fee $5,500.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see
Civil and Natural Resources Engineering.