COMP SCI 7211MELB - Foundations of Computer Science B

Melbourne Campus - Semester 2 - 2025

Introduces fundamental concepts of building data science applications in Python. Object oriented fundamentals x 001A methods, and classes. Algorithms and problem solving - problem solving processes and strategies. Computational complexity of algorithms. Software development tools and techniques - testing: black box, requirements. Representation and manipulation of large scale data sets.

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Course Details

Course Code	COMP SCI 7211MELB
Course	Foundations of Computer Science B
Coordinating Unit	Computer Science
Term	Semester 2
Level	Postgraduate Coursework
Location/s	Melbourne Campus
Units	3
Contact	Up to 6 hours per week
Available for Study Abroad and Exchange	N
Prerequisites	COMP SCI 7210; Master of Computing and Innovation students are permitted to enrol into COMP SCI 7210 and COMP SCI 7211 concurrently
Incompatible	COMP SCI 7202, COMP SCI 7208, COMP SCI 7103
Restrictions	Available only to University of Adelaide College Melbourne Campus students
Assessment	Assignments

Course Staff

Course Coordinator: Dr Menasha Thilakaratne

Course Timetable

The full timetable of all activities for this course can be accessed from Course Planner.

Learning Outcomes

Course Learning Outcomes

Upon completion of this course/subject, students will be able to:

Apply good programming style and understand the impact of style on developing and maintaining programs.
Effectively use a version control system and the Linux command-line tools for incremental development.
Implement, test and debug solutions in Python.
Identify the relative merits of different algorithmic designs.
Analyse algorithms and identify key algorithmic strategies.
Explain fundamental computing algorithms.

University Graduate Attributes

No information currently available.
Learning Resources

Recommended Resources

Zhang, Y., (2015), An Introduction to Python and Computer Programming (Links to an external site.)(Links to an external site.),,(1st ed. Lecture Notes in Engineering 353), Springer, London.

Lee, K., & Mackie, I., (2014), Python Programming Fundamentals (Links to an external site.) (Links to an external site.),(2nd ed. Undergraduate Topics in Computer Science), Springer, London.

Baka, B. (2017). Python Data Structures and Algorithms. Packt Publishing Ltd.

Lee, K. D., Lee, K. D., & Steve Hubbard, S. H. (2015). Data Structures and Algorithms with Python. Springer.

Textbooks are available to students as e-books through the Library.

Online Learning

All materials are available from MyUni and it is possible to work through most of the course activities on-site.
Learning & Teaching Activities

Learning & Teaching Modes

This course is structured around supported active learning labs. Assessment, discussions and support occur face to face. The materials are available online. Attendance at all sessions is not mandatory and can be negotiated with course coordinator during the first week.

Workload

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

This course assumes a commitment of 10-13 hours per week over 12 weeks.

Learning Activities Summary

The course is structured into four modules, each focusing on a range of skills, from fundamental shell commands to version control and software testing methodologies. Each module is designed to build on the skills and enhance the depth and breadth of knowledge in software development. The course includes a variety of learning methods, such as lectures, practical workshops, discussions, and assessments (practicals, quizzes, and section tests).

Module 1: Programming Environment & Configuration
Topics Covered: Introduction to Unix & the Shell, Shell Techniques & Tools, Basic Shell Scripting. This module provides foundational skills in navigating and operating within the Unix environment, along with scripting to automate tasks and streamline workflows.

Module 2: Programming Tools & Technique
Topics Covered: Introduction to Version Control, Git Basics, Git Branching and Merging, Git Remote Repositories & GitHub. Students learn to manage and collaborate on software projects using Git, emphasising version control fundamentals, collaborative features of Git, and integration with GitHub.

Module 3: Algorithms & Complexity
Topics Covered: Debugging, Exceptions & Static Analysis, Testing Basics, Testing Methodology. This module includes techniques for identifying and fixing bugs, using static analysis tools, and structured testing strategies to ensure software reliability and functionality.

Module 4: Data Structures & Algorithms
Topics Covered: Graph representation, object representation of a graph, Depth First Search (DFS), Breadth First Search (BFS), Dijkstra's algorithm, tree data structure, search with trees and tree maintenance. The purpose of this module is to understand essential complex data structures for efficient data organisation and problem-solving.

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 Summary

Assessment Task	Weighting (%)	Individual/ Group	Formative/ Summative	Due (Week)*	Hurdle criteria	Learning outcomes	CBOK Alignment**
Programming Practice	0%	Individual	Formative	Weekly		1 - 6	1.1 1.2 2.2 2.6 3.1 3.2 3.3 4.1 4.2 4.3
Section Tests	100%	Individual	Summative	4, 7, 10 & 13	85%	1 - 6	1.1 1.2 2.2 2.6 3.1 3.2 3.3 4.1 4.2 4.3
Total	100%

* The specific due date for each assessment task will be available on MyUni.
In accordance with the Assessment for Coursework Programs Policy, Procedure 1b: An exemption from the stated hurdle requirements has been granted.
This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.

**CBOK is the Core Body of Knowledge for ICT Professionals defined by the Australian Computer Society. The alignment in the table above corresponds with the following CBOK Areas:

1. Problem Solving
1.1 Abstraction
1.2 Design

2. Professional Knowledge
2.1 Ethics
2.2 Professional expectations
2.3 Teamwork concepts & issues
2.4 Interpersonal communications
2.5 Societal issues
2.6 Understanding of ICT profession

3. Technology resources
3.1 Hardware & Software
3.2 Data & information
3.3 Networking

4. Technology Building
4.1 Programming
4.2 Human factors
4.3 Systems development
4.4 Systems acquisition

5. ICT Management
5.1 IT governance & organisational
5.2 IT project management
5.3 Service management
5.4 Security management

Assessment Related Requirements

You must complete 4 specific modules as prescribed by your program of study.

Each module has a hurdle requirement, which is the module test. You need to achieve at least 85% on the module test to pass the module. You will have a limited opportunity to retake module tests that you do not pass in subsequent test weeks but these will be arranged in conjunction with the course coordinator in later testing weeks. If you don’t pass enough of the module tests, you may be required to take any or all of the modules again in a subsequent offering.

You will be required to demonstrate your ability to apply what you have learnt each week in the creation of programs to solve practice problems to be eligible to sit for the module test.

Successful completion of an appropriate set of modules will result in a Non-Graded Pass (NGP) in this course.

Assessment Detail

No information currently available.

Submission

No information currently available.

Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

GS8 (Coursework Grade Scheme)
Grade	Description
CN	Continuing
FNS	Fail No Submission
NFE	No Formal Examination
F	Fail
NGP	Non Graded Pass
P	Pass
C	Credit
D	Distinction
HD	High Distinction
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.

Student Feedback

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.
Student Support
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator