COMP SCI 7211 - Foundations of Computer Science B

North Terrace Campus - Semester 2 - 2024

Introduces fundamental concepts of building data science applications in Python. Object oriented fundamentals x001A 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.

  • General Course Information
    Course Details
    Course Code COMP SCI 7211
    Course Foundations of Computer Science B
    Coordinating Unit Computer Science
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange
    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
    Assessment Assignments
    Course Staff

    Course Coordinator: Matthew Brennan

    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

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    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.

  • 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
    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
    This course assumes a commitment of 20-25 hours per week over each week.

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

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
    This course assumes a commitment of 20-25 hours per week over each week.
    Learning Activities Summary
    Unix/Subversion basics, use of libraries, variables, constant, string literals, expressions, operators, basic types /representation, conditionals/loops, functions, basic I/O, algorithms and program structure, coding style.
    Arrays, vectors and structs, number representation, pointers and dynamic storage, memory allocation and freeing, call by reference, call by pointer, call by value , testing and defensive programming.
    Programming languages and paradigms, procedural vs object oriented design, class definitions, class members, class methods / procedures, class implementations.
    Overloading operators and methods, copy constructors, static class members.
    Class hierarchies, inheritance, multiple inheritance, polymorphism, namespaces.
    Recursion, evaluating algorithms memory and runtime, algorithmic approaches to searching (linear and binary), sorting.
    Programming data structures: stacks, queues, linked lists.
    Trees, algorithmic strategies, review.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%)
    Due (Week)*
    Hurdle criteria Learning outcomes CBOK Alignment**
    Programming Practice 0% Individual


    Weekly 1 - 6 1.1 1.2 2.2 2.6 3.1 3.2 3.3 4.1 4.2 4.3
    Module 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.

    All submissions must be made through MyUni. Follow the assessment links for each assessment item.
    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 ( 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
  • 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.

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