Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2015:Semester 1, Parkville - Taught on campus.
Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 60 hours, comprising of three 1-hour lectures and one 2-hour workshop per week |
Total Time Commitment:
Study Period Commencement:
Semester 1, Semester 2
Achieving at least 75% in a programming competency test.
|Recommended Background Knowledge:|| |
|Non Allowed Subjects:||
Students cannot enrol in and gain credit for this subject and:
433-172 Algorithmic Problem Solving
433-152 Algorithmic Problem Solving
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorDr Ben Rubinstein, Prof Alistair Moffat
Semester 1: Dr Benjamin Rubinstein
Semester 2: Professor Alistair Moffat
In many projects, it is important for programmers to have fine control over low-level details of program execution, and to be able to assess the cost of a design decision on likely overall program performance. This subject introduces students to a system programming language that gives programmers this kind of control, explores a range of standard data structures and algorithmic techniques, and shows how to apply them to frequently encountered problems.
INTENDED LEARNING OUTCOMES (ILO)
Hurdle requirement: To pass the subject, students must obtain at least:
Intended Learning Outcomes (ILO) 1 is addressed in all components of assessment. ILO 2, ILO 3, ILO 4 and ILO 5 are assessed in the mid-semester test and in the examination. ILO 6 is addressed in the programming assignments.
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subject students should have developed the following skills:
This subject is available for science credit to students enrolled in the BSc. Students undertaking this subject will require regular access to the internet.
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, programming workshops, and programming exercises and assessed programming assignments. Students will also be expected to develop and submit programming assignments for assessment.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes and lecture slides, and will be expected to own a copy of the textbook nominated by the coordinator. Other guidance will be provided via the LMS.
CAREERS / INDUSTRY LINKS
Programming competencies are a critical part of a range of career pathways, including in IT, engineering, and mathematics. In addition, an understanding of the fundamental nature of computation is a key enabler across all science discipline areas, including genetics and physics.
Science-credited subjects - new generation B-SCI and B-ENG. |
Selective subjects for B-BMED
|Related Breadth Track(s):||
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