COMP SCI 2009MELB - Programming for IT Specialists
Melbourne Campus - Semester 1 - 2024
General Course Information
Course Code COMP SCI 2009MELB Course Programming for IT Specialists Coordinating Unit Computer Science Term Semester 1 Level Undergraduate Location/s Melbourne Campus Units 3 Available for Study Abroad and Exchange Prerequisites COMP SCI 1015UACM Incompatible COMP SCI 1102, COMP SCI 1202, COMP SCI 2202, COMP SCI 2202B Restrictions Available only to University of Adelaide College Melbourne Campus students Course Description Programming for IT Specialists builds on the programming knowledge developed in COMP SCI 1015 and provides students with a solid coding foundation to undertake Information Technology work at the professional level. Students are introduced to multiple object-orientated languages that are heavily used for systems work, including compiled and interpreted languages, as well as the data structures and algorithms vital to working in the systems area. Students will develop be assessed through programming assignments, weekly quizzes, project work, and a final examination. The course uses current technology and real examples to provide an authentic and useful development environment.
Course Coordinator: Mr Arie Bennett
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes
On successful completion of this course students will be able to: 1 Use Unix-based tools and BASH scripts to carry out system tasks 2 Explain the benefits of object oriented design and understand when it is an appropriate methodology to use 3 Design object oriented solutions for small systems involving multiple objects 4 Implement, test and debug solutions in Python and C++ 5 Manage memory usage in C/C++ programs 6 Explain fundamental computing algorithms 7 Analyse algorithms and identify key algorithmic strategies, and 8 Explain and apply regular expressions for common system tasks
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
Required ResourcesThe only required text for this course is Grokking Algorithms by Aditya Y. Bhargava. All other materials will be provided through the University's Learning Management System, MyUni.
Recommended ResourcesThe University provides computers on campus for students but remote students may find it useful to have access to a Linux computing environment, whether directly on their machine, via virtualisation, or using the Windows Subsystem for Linux v2. While there are many excellent online resources, students may also find it useful to consult any of the following books as a reference:
- Bash Guide for Beginners. (By Machtelt Garrels)
- Advanced Bash Scripting Guide. (By Mendel Cooper)
- Tutorial: programming in C, UNIX system calls and subroutines using C. (By A. D. Marshall)
Learning & Teaching Activities
Learning & Teaching ModesThis course has three contact activities: lectures, workshops and practicals. Each of these activities is used to support and build on each other.
Lectures: Weekly delivery of new material. These are scheduled for a duration of 2 hrs, with a 10 minute recess. Remote options are provided as all lectures are livestreamed and recorded through Echo360, available through MyUni.
Workshop sessions: Interactive sessions with your tutor and peers where you will be presented with new material and/or exercises that you will complete and submit in the session. Depending on the week, workshops give you an opportunity to practice the theory or practical skills relavant to that week's material.
Practical sessions: Support sessions provided to get help on that week's content, either coding or theory. No new material is introduced during these sessions. Instead, they are provided to give you a dedicated time block to get support from your tutor. During weeks 6 and 12 you will take your practical exams here instead. During these exam sessions, attendance is necessary to undertake the exam.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.Students are expected to spend approximately 10 hours per week on this course. A typical week will involve 5-6 contact hours for learning and teaching activities and 4-5 hours of independant study. Independant study includes, reading the required reading, completing assessments, content revision and self-driven programming practise.
Learning Activities Summary
Week Topic 1 Introduction to algorithms 2 Divide & conquer 3 Hash tables 4 Graphs 5 Dynamic programming and greedy algorithms 6 Review and exam week 7 Introduction to C++ 8 Pointers 9 Memory Model 10 OOP 11 Inheritance & Polymorphism 12 Other Programming languages and exam week
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Task Type Due Weighting Learning Outcome Workshop participation* Summative
Weekly, except Weeks 6 & 12
5% 1,2,3,4,5,6,7,8 Workshop exercises* Summative Weekly, except Weeks 6 & 12 10% 1,2,3,4,5,6,7,8 Coding exercises Summative Weekly, except Weeks 6 & 12 15% 3,4,5 Practical exams Summative Weeks 6 & 12 40% 3,4,5 Final exam Summative Exam period 30% 2,3,6,7
Assessment DetailWorkshop participation (5%): Each workshop involves both active participation and a submission exercise. To demonstrate active participation, you must have completed the preparatory quiz before the session and contribute towards the session's class discussion. You do not earn a mark for simply attending!Workshop exercises (10%): Each workshop involves both active participation and a submission exercise. The submission exercises are extentions of the workshop activities designed to assess your understanding of the newly introduced material and give you feedback on your progress. Some workshops focus on theory, where as others are practical focused.
You will submit the required files to Gradescope before you leave your session. More infromation will be available on MyUni for more details regarding these workshops.Coding exercises (15%): Each week you must complete some coding exercises. These are your opportunity to practice and recieve feedback on your understanding of the practical concepts discussed in the course and your ability to implement and use algorithms and data structures to solve problems. You must work individually on all practicals.Practical examinations (40%): During weeks 6 and 12, you have your practical exams. These will take place during your regularly scheduled practical session. You must attend these sessions. Failure to do so will earn you a zero. See MyUni for further detail.
Final examination (30%): During the exam period you will have a final written exam that will assess your overall understanding of the course. See MyUni for further detail.
70% of your mark will come from assessments conducted under exam conditions. There are no hurdle assessments in this course.
SubmissionStudents will submit their code to Gradescope where it will be marked by their tutor and/or automatically using an auto-grader depending on the assessment (students are taught how to use this system in the course). Quizzes will be automatically marked in MyUni.
Failure to submit an assessment item on time or by the agreed extension deadline will result in penalties. For each day or part-day that a programming assignment is late, the maximum mark that can be awarded is reduced by 25%.
Any request for an extension of time for the submission of an assessment item should be made well before the due date to the Course Coordinator. Normally, extensions will only be granted for a maximum of two weeks from the original assignment submission date. Extensions will only be granted in cases of genuine extenuating circumstances and evidence, such as a medical certificate, must be provided.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.This course is running for the first time in 2021. There are no previous SELT results to display.
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This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
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- Student Experience of Learning and Teaching Policy
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