Bachelor of Computing

The Bachelor of Computing qualification's objective is to equip learners with theoretical knowledge and associated practical skills. The qualification will provide learners with a good theoretical and practical basis for working in the information and communication technology (ICT) industry including (but not limited to) application and software development, database administration, systems analysis, software testing, big data analytics, and machine learning implementation.

This qualification is intended to prepare learners for employment in a variety of business contexts, by developing their ability to identify problems in a wide variety of disciplines and apply appropriate algorithms, tools, and techniques to solve these.

The proposed curriculum for this qualification will prepare learners to enter the workplace equipped with sufficient problem-solving skills, technical knowledge and practical programming experience to play a meaningful role in the South African economy.

Learners who successfully complete the Bachelor of Computing qualification will demonstrate competence in both theoretical knowledge and practical application, through a combination of practical projects. Having completed the Bachelor of Computing Degree, learners will be well positioned to take up virtually any position in the ICT field (even if this is not directly linked to the degree content) and contribute purposefully to the South African economy.

The typical learner identified to benefit from this qualification is an individual who has studied IT at school or who has entry-level IT work experience and would like to upgrade their knowledge, skills and competencies to a more senior level. However, the qualification is also suitable for graduates from other disciplines who wish to move into the IT field. Individuals who lack previous IT experience may gain admission to the Bachelor of Computing programme by first completing the Higher Certificate in Software Development.

Upon completion of the qualification, a qualifying learner will be able to

• Demonstrate an understanding of the theoretical foundations of computing and its relevance to everyday computing.
• Apply computational thinking, analytical reasoning and problem-solving skills to find innovative solutions for industry problems.
• Implement solutions using appropriate development and testing tools, including a variety of programming paradigms and the corresponding programming languages.
• Apply appropriate mathematical and statistical concepts and skills to interpret and analyse data.
• Apply secure computing principles and techniques to identify and assess potential risks affecting the security of software applications and the ICT infrastructure.

Rationale

According to the 2021 ICT Skills Survey, the impact of the COVID-19 pandemic has exacerbated this situation leaving nearly 10 000 vacant positions in the ICT section. With information and communication technology (ICT) evolving ever faster, accompanied by new paradigms involving more complex algorithms, optimized programming, and greater execution efficiency, the need for computer scientists who can understand and leverage the new technology and paradigms grows daily. Being able to write code is no longer a sufficient basis on which to leverage the continual hardware improvements and algorithmic advances. The following quote alludes to this continually changing workplace for computer scientists.

The current need within the ICT industry for a skilled workforce has not been fulfilled effectively and sufficiently. The industry requires graduates who are well-prepared to operate within the envisaged 4th Industrial Revolution with analytical skills, critical problem-solving abilities, and expert computer knowledge that will render the industry (and organisations within the industry) relevant, profitable and sustainable.

The qualification aims to provide a good theoretical and practical basis for working in the ICT industry and a solid foundation for future learning, which is inevitable in this evolving field. The knowledge that learners obtain from this degree would benefit numerous ICT professions, including application and systems software development, database administration, systems analysis, software testing, big data analytics, machine learning implementation, and many more.

This qualification is intended to prepare Bachelor of Computing graduates for employment in a variety of business contexts, by developing their ability to identify problems in a wide variety of disciplines and apply appropriate algorithms, tools, and techniques to solve these. This is particularly relevant to the South African context, where the technical skills needed to support the envisaged 4th Industrial Revolution are perceived to be some of the scarcest skills in South Africa. Board members of the Institute of Information Technology Professionals South Africa (IITPSA) claim that skills shortages are the single biggest challenge facing the South African IT sector in the next ten years.

A Bachelor of Computing qualification will equip learners for a broad range of careers in ICT including.

• Application and systems software development.
• Database administration.
• Systems analysis.
• Big data analytics.
• Machine learning implementation.

Recognition of Prior Learning (RPL)

RPL for access

Note that RPL and CAT are applied per separate policies.

Applicants who do not meet the stated admission criteria, but who have relevant work experience/prior learning may apply for admission under the policy on Recognition of Prior Learning (RPL). The institution admits a maximum of 10% per cohort via RPL. The implementation of RPL is context-specific, in terms of discipline, programme and level. Procedures and forms are available from the School Administration.

In specified circumstances, qualifying applicants may also engage in the RPL for exemption process, where any form of informal, formal or non-formal learning will be assessed for relevance towards possible module exemption.

Entry Requirements

The minimum entry requirement for this qualification is

• National Senior Certificate (NSC), NQF Level 4, granting access to Bachelor's degree studies 4.

or

• Senior Certificate, NQF Level 4 with endorsement.

or

• National Certificate (Vocational), NQF Level 4 granting access to Bachelor's degree studies.

or

• Higher Certificate in a cognate field of study, NQF Level 5.

or

• Advanced Certificate in a cognate field of study, NQF Level 6.

or

• Diploma in a cognate field of study, NQF Level 6.

This qualification consists of the following compulsory and elective modules at National Qualifications Framework Levels 5, 6 and 7 totalling 360 Credits.

Compulsory Modules, Level 5, 120 Credits

• Fundamentals of Information Technology, 10 Credits.
• Technology and Society, 10 Credits.
• Computational Thinking and Introduction to Programming, 20 Credits.
• Introduction to Databases, 10 Credits.
• Software Development, 10 Credits.
• Object-Oriented Programming, 15 Credits.
• Discrete Mathematics, 15 Credits.
• Introduction to Statistics, 15 Credits.
• Electronics for Computing, 15 Credits.

Compulsory Modules, Level 6, 100 Credits

• Advanced Programming and Algorithm Analysis, 15 Credits.
• Computer Architecture, 10 Credits.
• Web and Mobile Development, 15 Credits.
• Object-Oriented Analysis, 10 Credits.
• Computer Networks, 10 Credits.
• Operating Systems, 10 Credits.
• Automata and Formal Languages, 10 Credits.
• Fundamentals of Data Analytics, 20 Credits.

Elective Modules, Level 6, 20 Credits (Select one module)

• Object-Oriented Design, 20 Credits.
• Information Systems Project Management, 20 Credits.
• Virtual Systems and Services, 20 Credits.
• Cloud Computing, 20 Credits.

Compulsory Modules, Level 7, 120 Credits

• Integrated Research Project (with societal impact), 30 Credits.
• Research Principles, 10 Credits.
• Information Security and Cybersecurity, 15 Credits.
• Programming Paradigms, 10 Credits.
• Programming Language Implementation, 15 Credits.
• Introduction to Parallel Computing, 20 Credits.
• Introduction to Artificial Intelligence, 20 Credits.

1. Demonstrate an understanding of the theoretical foundations of computing and its relevance to everyday computing.
2. Apply computational thinking, analytical reasoning and problem-solving skills to find innovative solutions for industry problems.
3. Implement solutions using appropriate development and testing tools, including a variety of programming paradigms and the corresponding programming languages.
4. Apply appropriate mathematical and statistical concepts and skills to interpret and analyse data.
5. Apply secure computing principles and techniques to identify and assess potential risks affecting the security of software applications and the ICT infrastructure.
6. Employ existing knowledge of fundamental programming constructs in a variety of imperative and functional programming languages to facilitate the learning of new programming languages.
7. Conduct research to understand new algorithms, tools and techniques to address the challenges of emerging technologies and methodologies.
8. Apply awareness of the ethical and cultural values in designing, implementing and using ICT applications.

Associated Assessment Criteria for Exit Level Outcome 1

• Differentiate common computational problems in terms of decidability and tractability.
• Apply theoretical concepts of computing to the practice of program design with regular expressions, parsing, and complexity analysis.

Associated Assessment Criteria for Exit Level Outcome 2

• Apply problem-solving (including computational thinking) and programming skills to design solutions to non-trivial problems.
• Model a software system using appropriate object-oriented techniques for systems analysis including relevant UML diagrams.
• Apply appropriate techniques and algorithms, including the application of Artificial Intelligence, to solve real-world problems.
• Analyse, design, and integrate networking into applications.

Associated Assessment Criteria for Exit Level Outcome 3

• Identify a suitable linear, tree, or hashed data structure and correctly apply the operations associated with it to solve a real-world problem.
• Design and operate a von Neumann architecture and the interface provided to execute systems and application software.
• Illustrate an understanding of human-computer interaction in designing user-friendly websites and mobile applications.
• Illustrate an understanding of the various primitives, together with the benefits of each, employed at the operating system level to implement concurrent processes.
• Participate in a software development team, based on agreed roles and responsibilities.

Associated Assessment Criteria for Exit Level Outcome 4

• Apply appropriate counting techniques such as additive and multiplicative rules, combinations and permutations, and progressions, to real-world applications.
• Apply estimation and testing methods to analyse single variables or the relationship between two variables to make data-based decisions.
• Model numerical response variables using a single explanatory variable or multiple explanatory variables to investigate relationships between variables.
• Suggest ways in which data analysis techniques can be used to create enhanced decision-support dashboards.
• Interpret results correctly, effectively, and in context without relying on mathematical or statistical jargon.

Associated Assessment Criteria for Exit Level Outcome 5

• Identify common threats affecting information security at the human, physical, network and application levels; and outline preventative measures that can be used to eliminate or manage these threats.
• Evaluate network security solutions, Internet crimes, and cloud computing methodology to prevent and detect intrusions.
• Analyse and evaluate systems with respect to maintaining operations in the presence of risks and threats.

Associated Assessment Criteria for Exit Level Outcome 6

• Illustrate an understanding of the syntax and semantic features of programming languages in general.
• Formally express the key characteristics of the various programming paradigms and explain the advantages and disadvantages of each for a given programming purpose.
• Select the most appropriate programming language to solve a given problem, justifying the choice based on the characteristics of the respective paradigm.

Associated Assessment Criteria for Exit Level Outcome 7

• Conduct a comprehensive literature search to understand the underlying concepts in the identified research area and existing solutions to an identified problem.
• Apply the scientific method to solve the identified problem.
• Develop, implement and demonstrate a working prototype of a proposed solution and present the findings.

Associated Assessment Criteria for Exit Level Outcome 8

• Illustrate an understanding of the ethical challenges posed by artificial intelligence.
• Contribute to the maintenance of the Internet and world of technology.

INTEGRATED ASSESSMENT

There are two assessment models, namely a final summative approach, as well as a continuous assessment approach. The assessment model of a module is selected based on the nature of the module outcomes, as well as its level and function in the overall curriculum.

Where a final summative approach is used, the final mark on a module comprises a Semester/Year Mark (SYM) that contributes 50% of the final mark, as well as a Final Summative Assessment mark (FIS) that contributes 50%.

The Semester Mark (SYM) is made up of a range of different assessment tasks (SF1, SF2), each with its own weighting.

The Final Summative (FIS) is often in the form of an invigilated examination, but it may be offered in alternative formats, such as an individual/group project which culminates in a written report, followed up by a presentation.

In cases where a continuous assessment approach is used, the FIS is replaced by a series of weighted formative and summative assessments (SS1, SS2, etc.) that take place throughout the semester/year. The detail on the structure for each module is indicated in the Module Outline document.