All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source. |
SOUTH AFRICAN QUALIFICATIONS AUTHORITY |
REGISTERED QUALIFICATION: |
Postgraduate Diploma in Artificial Intelligence |
SAQA QUAL ID | QUALIFICATION TITLE | |||
119095 | Postgraduate Diploma in Artificial Intelligence | |||
ORIGINATOR | ||||
MANCOSA Pty (Ltd) | ||||
PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY | NQF SUB-FRAMEWORK | |||
- | HEQSF - Higher Education Qualifications Sub-framework | |||
QUALIFICATION TYPE | FIELD | SUBFIELD | ||
Postgraduate Diploma | Field 10 - Physical, Mathematical, Computer and Life Sciences | Information Technology and Computer Sciences | ||
ABET BAND | MINIMUM CREDITS | PRE-2009 NQF LEVEL | NQF LEVEL | QUAL CLASS |
Undefined | 120 | Not Applicable | NQF Level 08 | Regular-Provider-ELOAC |
REGISTRATION STATUS | SAQA DECISION NUMBER | REGISTRATION START DATE | REGISTRATION END DATE | |
Registered | SAQA 158/22 | 2022-04-21 | 2025-04-21 | |
LAST DATE FOR ENROLMENT | LAST DATE FOR ACHIEVEMENT | |||
2026-04-21 | 2029-04-21 |
In all of the tables in this document, both the pre-2009 NQF Level and the NQF Level is shown. In the text (purpose statements, qualification rules, etc), any references to NQF Levels are to the pre-2009 levels unless specifically stated otherwise. |
This qualification does not replace any other qualification and is not replaced by any other qualification. |
PURPOSE AND RATIONALE OF THE QUALIFICATION |
Purpose:
The purpose of this Postgraduate Diploma in Artificial Intelligence is to provide learners with advanced skills and knowledge spanning a wide range of areas in Artificial Intelligence (AI). Artificial Intelligence aims to make computers and information systems more "intelligent" to solve complex problems and provide more natural and effective services to human beings. Artificial Intelligence has been a source of innovative ideas and techniques in information technology fields. This qualification provides a comprehensive understanding of the core areas of Artificial Intelligence (AI). Learners will obtain both theoretical and practical knowledge and skills needed to design, build and apply AI systems in various organisational contexts. The growth of AI and its use in the development of systems that can reason and respond to increasingly complex situations has exploded. This advancement results in an increased demand for individuals who can create complex systems that can partner with, rather than replace or even augment, human users. The qualification aims to serve this demand by producing qualified learners who have exceptional technical skills to create new AI systems and understand the nature of the human environments in which the systems they build will be deployed. The qualification is designed for information technology (IT) graduates and people working in information technology-related fields and provides the knowledge and skills IT professionals need to work with big data. The qualification aims to facilitate an exploration of state-of-the-art knowledge of the core areas of AI, production of insightful and innovative ideas, solutions to complex problems and optimal application of AI systems. This will be the corollary of the knowledge depth obtained from this broad-based and industry-focused curriculum. Upon completion of this qualification, qualifying learners will be able to: The graduate attributes will include the following: intelligence systems that critically contribute to the development of ethical standards in the field of artificial intelligence. Rationale: The advent of The Fourth Industrial Revolution (4IR) has thrust societies into a new world of technological advancement and rapid change. The 4IR is being powered by technologies, such as Artificial Intelligence (AI). These societal changes are manifested in the way people live, work and relate with one another and the environment. At the Salzburg Global Seminar, Sparvell (2018) admitted that AI is bridging social and cultural divides in workplaces and people's everyday lives in today's societies. AI is transforming government, delivering health care, creating art and creating new jobs. Frantz (2019) mentioned that even though repetitive jobs will be lost due to intelligence systems, many more new jobs will be created in the same vein. The new jobs are more engaging and less repetitive, hence creating a perfect opportunity for workers to focus on the parts of their jobs that may be the most satisfying to them. This in turn increases productivity and builds strong economies. In order to create a workforce that is capable to drive this new economy, the qualification is designed to produce graduates that have the most in-demand knowledge and expertise of AI. Lauterbach (2018) observed that AI brings layers of problem-solving into any business environment. Training people and equipping them with the next generation's skills means that societies are empowered to solve the most complex problems. Lauterbach further argues that given that the nature of jobs is changing at a rapid pace, a broader societal dialogue is needed around education and preparing for the future. The World Economic Forum (2019) announced that AI and Cloud Computing are the two most in-demand hard skills in 2019. This qualification coincides with the expectation of the World Economic Forum, for appropriate qualifications to be created to meet the skills demand. As technology continues to change at a rapid pace, AI has become a part of the fabric of society and a glue that holds society together as technology becomes more ubiquitous and pervasive. Dogson and Gann (2017) stressed that AI is a technology whose time has come, as it has surpassed human abilities in every aspect. They also indicated that AI is a new scientific infrastructure for research and skills acquisition that academic institutions must embrace and lead, lest they become increasingly irrelevant and eventually redundant. How the institutions of learning respond to this AI revolution will profoundly reshape education, innovation and society itself. The qualification goes to the core of AI by incorporating knowledge areas, such as machine learning, computer vision and computational intelligence that adequately equip learners with the essential skills and competencies to be able to build AI-powered intelligent solutions for the highly dynamic and increasingly complex problems of our time. The institution facilitates distance delivery, which allows learners to either retain their full-time employment or seek employment to complement their academic journey. Learners are provided with a plethora of support from e-learning platforms to assist the learning journey, an information management system that manages the learning process and provides learners with the necessary academic material and support, face-to-face workshops and consultation with lecturers. The Fourth Industrial Revolution (4IR) is profoundly permeating and affecting all elements of contemporary societies and economies. The combination of technologies in AI and Machine Learning (ML) requires a suite of skills that can match the complexity and the innovativeness inherent in these intelligent systems. Presently, AI is increasingly integrated into people's everyday lives with personal assistants. AI applications and intelligent machines like Siri, Alexa, Watson, Cortana, LinkedIn, and Google AI Assistant are all popular applications that are used to conduct everyday tasks. These assistants can be used to pull information from the web, turn on home appliances, set reminders, talk to each other, and so much more. These types of machine learning and intelligent systems assistants are ever-evolving, so the demand for AI specialists and professionals is at an all-time high for this market and industry. The AI skill appetite cuts across various platforms, whether Microsoft Windows, iOS, an open-source platform, Google, or Android, the demand for skills remains high. In many sectors of the South African economy, machines have already taken over monotonous jobs. Manufacturing and banking are prime examples. The primary goals of implementing AI solutions in these sectors include speeding up repetitive procedures by using robots or machines instead of humans, out-smarting human brains through "learning" and memory, and recognising patterns to make decisions instantly and efficiently. The purpose of the qualification is to ensure that learners are equipped to develop these solutions and be relevant in today's AI-augmented workplace. AI has also become a specialisation out of the traditional computer science and information technology qualifications, this is because AI has increasingly become a giant paradigm shift in modern computing and therefore requires a deeply scientific and logical approach to design computer systems that think and learn. |
LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING |
Recognition of Prior Learning (RPL):
The institution has an approved Recognition of Prior Learning (RPL) policy applicable to equivalent qualifications for admission into the qualification. RPL will be applied to accommodate applicants who qualify. RPL thus provides alternative access and admission to qualifications, as well as advancement within qualifications. RPL may be applied for access, credits from modules and credits for or towards the qualification. RPL for access: RPL for exemption of modules: RPL for credit: Entry Requirements: The minimum entry requirement for this qualification is: Or Or Or Or Or Or |
RECOGNISE PREVIOUS LEARNING? |
Y |
QUALIFICATION RULES |
This qualification consists of the following compulsory modules at National Qualifications Framework Level 8 totalling 120 Credits.
Compulsory Modules, Level 8, 120 Credits |
EXIT LEVEL OUTCOMES |
1. Demonstrate the ability to use a range of specialised skills to identify, analyse and address complex or abstract problems drawing systematically on the body of knowledge and methods appropriate to a field, discipline or practice.
2. Demonstrate knowledge of and engagement in an area at the forefront of a field, discipline or practice; an understanding of the theories, research methodologies, methods and techniques relevant to the field, discipline or practice; and an understanding of how to apply such knowledge in a particular context. 3. demonstrate the ability to critically review information gathering, synthesis of data, evaluation and management processes in specialised contexts in order to develop creative responses to problems and issues. 4. Demonstrate the ability to use a range of specialised skills to identify, analyse and address complex or abstract problems drawing systematically on the body of knowledge and methods appropriate to a field, discipline or practice. 5. Evaluate organisational strategy, policies, and procedures in respect of AI and ensure they address all facets of AI and are integrated and aligned to enable the organisation to achieve its AI aspirations. |
ASSOCIATED ASSESSMENT CRITERIA |
Associated Assessment Criteria for Exit Level Outcome 1:
Associated Assessment Criteria for Exit Level Outcome 2: Associated Assessment Criteria for Exit Level Outcome 3: Associated Assessment Criteria for Exit Level Outcome 4: Associated Assessment Criteria for Exit Level Outcome 5: INTEGRATED ASSESSMENT The nature of assessment and feedback to learners serves as an important factor when evaluating learners' learning experience and the institution has adopted an effective assessment strategy that uses multiple components. The institution has recognised a change in its learner profile and more significantly in the learning needs of learners, nationally and internationally. There have been a number of advancements in education technology that better supports learner success. In pursuit of global relevance and enhanced learner success, the institution has taken the decision to participate in this global trend and will initiate the natural progression from distance to online for its qualifications and in doing so, the institution has undertaken a review of its strategy. Formative assessment: Formative assessment consists of knowledge checks, reflective assessments and learning community assessment. Knowledge checks may comprise matching columns, multiple-choice questions, true and false and drag and drop assessment methods. Reflective assessments may consist of a short essay, long essay/case studies and posting comments/peer review. A formative process through which learners can experience assessment as a part of learning, rather than as a separate evaluative process. This includes short essays and long essays/cases studies. The projects and case studies (formative assessments) at this level are structured in such a way that it requires learners to practice and demonstrate a number of higher-order skills, including the ability to articulate, evaluate and appropriately use evidence. These projects generally have a strong research focus geared toward preparing the learner for Master's level study. The scheme of work includes assignments based on the learning material and learners are given feedback. The process is continuous and focuses on smaller sections of the work and a limited number of outcomes. Summative assessment: Examinations or equivalent assessments such as a research essay or portfolio to determine a representative selection of the outcomes practised and assessed in the formative stage. Summative assessment also tests the learner's ability to manage and integrate a large body of knowledge to achieve the stated outcomes of a module. Summative assessment consists of projects, pen/paper exams, a portfolio of evidence and a dissertation. The summative assessments carry a 60% weighting and comprise module projects or examinations, which requires learners to demonstrate immediate connections between theories, concepts, and skills and their immediate utility in current or future career scenarios. Completing module projects provides evidence of high-level cognitive skills (i.e. creation, application, analysis, and evaluation) and requires learners to strategise and plan how to approach complex problems that are relevant to the proposed scenario. |
INTERNATIONAL COMPARABILITY |
The South African qualification is internationally comparable with similar qualifications offered by the following international countries.
Country: Sri Lanka Institution: University of Moratuwa Qualification Title: Postgraduate Diploma in Artificial Intelligence Purpose of Qualification: The purpose of the Postgraduate Diploma in Artificial Intelligence at the University of Moratuwa is to impart the knowledge of theory and applications of modern Artificial Intelligence technologies to devise intelligent software solutions for tomorrow's world thereby ensuring multifaceted career paths for potential candidates. Qualification structure: Similarities: Both qualifications have a duration of one year. They embed new technologies and trends in artificial intelligence, as well as a research project to allow learners to develop research capacity in areas of artificial intelligence. The curriculum offered by the University of Moratuwa is similar to the curriculum offered by the South African qualification, especially in areas such as Computational Intelligence, Machine Learning, Multi-agent systems and programming for artificial intelligence. Differences: The qualification for the University of Moratuwa contains elective modules, whereas the South African qualification contains only core modules. The South African qualification is offered via distance learning mode, whereas the University of Moratuwa's qualification is offered in contact learning mode. Country: United Kingdom (UK) Institution: Heriot Watt University Qualification Title: Postgraduate Diploma in Artificial Intelligence Purpose of Qualification: The purpose of the Postgraduate Diploma in Artificial Intelligence is to impart the understanding and skills to develop intelligent software applications, such as those involving evolutionary computation and learning. Learners will develop skills in specialist areas with clear applications in the industry, including pattern recognition and machine learning. The final project enables learners to apply the knowledge of artificial intelligence to solve industrial problems. Qualification structure: Similarities: The UK qualification contains modules such as Artificial Intelligence and Intelligent Agents, Biologically Inspired Computation, Advanced Software Engineering, Data Mining and Machine Learning, 3D Graphics and Animation and Research Methods and Project Planning, which relate favourably with content in the South African qualification, such as Multi-Agent Systems, Computational Intelligence, Programming, Machine Learning, Computer Vision and Research Project respectively. In addition, both qualifications have a research project, which enables further development and consolidation of skills introduced in the taught courses, applying them to a challenging practical problem in the subject areas of Artificial Intelligence. Differences: The South African qualification has a duration of one year, whereas the Heriot Watt University's qualification has a duration of nine months. The Postgraduate Diploma in Artificial Intelligence offered by Heriot Watt University contains elective modules, whereas the South African qualification contains only core modules. The South African qualification is offered via distance learning mode, whereas Heriot Watt University's qualification is offered via contact learning mode. Country: Singapore Institution: Emeritus Institute of Management Qualification Title: Postgraduate Diploma in Machine Learning and Artificial Intelligence Purpose of Qualification: Artificial intelligence and machine learning algorithms are transforming systems, experiences, processes, and entire industries. It's no wonder that business leaders see these data-driven technologies as fundamental for the futureand that practitioners fluent in both fields are in high demand. The Emeritus Institute of Management is fascinated by the world-changing potential of Artificial Intelligence, and Postgraduate Diploma in Machine Learning and Artificial Intelligence qualification is purposed to help learners understand the fundamentals of Artificial Intelligence and Machine Learning and how to apply them to solve complex real-world problems. Qualification structure: Similarities: The modules and content in the Emeritus Institute of Management's qualification are related to modules and content in the South African qualification. For example, Intelligence Agents and Uninformed Search, Heuristic Search, Reinforcement Learning, AI applications: Natural Language Processing and Applied Machine Learning are related to the South African qualification modules, such as Multi-Agent Systems, Computational Intelligence, Programming, Machine Learning and Computer Vision. Differences: The Emeritus Institute of Management's qualification has a duration of nine months, whereas the South African qualification has a duration of 12 months. The South African qualification is more practical and research-oriented to the extent that it offers programming as a core module to provide a firm grounding in Python, while the Postgraduate Diploma in Machine Learning and Artificial Intelligence for Emeritus Institute of Management expects learners to possess knowledge of Python programming. |
ARTICULATION OPTIONS |
This qualification allows possibilities for both vertical and horizontal articulation.
Horizontal Articulation: Vertical Articulation: |
MODERATION OPTIONS |
N/A |
CRITERIA FOR THE REGISTRATION OF ASSESSORS |
N/A |
NOTES |
N/A |
LEARNING PROGRAMMES RECORDED AGAINST THIS QUALIFICATION: |
NONE |
PROVIDERS CURRENTLY ACCREDITED TO OFFER THIS QUALIFICATION: |
This information shows the current accreditations (i.e. those not past their accreditation end dates), and is the most complete record available to SAQA as of today. Some Primary or Delegated Quality Assurance Functionaries have a lag in their recording systems for provider accreditation, in turn leading to a lag in notifying SAQA of all the providers that they have accredited to offer qualifications and unit standards, as well as any extensions to accreditation end dates. The relevant Primary or Delegated Quality Assurance Functionary should be notified if a record appears to be missing from here. |
NONE |
All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source. |