Bachelor of Science in Data Science
Physical, Mathematical, Computer and Life Sciences - Information Technology and Computer Sciences
Purpose and Rationale
Purpose:
The purpose of the Bachelor of Science in Data Science is to develop learners who are able to demonstrate:
- An understanding of the basic physical principles as well as the basic statistical concepts and its applications.
- An understanding of the fundamental design, analysis, and implementation of basic data structures and algorithms, the analysis and evaluation of the data structure needs of particular problems, as well as gaining hands-on experience in the design, analysis, and implementation of C programmes by using basic data structures and algorithms.
- A theoretical background and understanding of how computer hardware functions and the competence to relate to his/her computer programme algorithm development and implementation to an efficient and optimal execution of the code in the hardware.
- An understanding of core aspects of information System (IS), focusing on the knowledge, skills and processes involved in developing and/or acquiring information systems.
- A solid understanding of fundamental architectural techniques used to build high-performance processors and systems.
- The Bachelor of Science in Data Science has a strong mathematical core and a focus on data science and applications thereof. The Degree is designed to develop highly skilled learners in areas in the field of data science. Learners will be equipped to deal with large data, understand and analyse systems, and have the mathematical and information technology skills to be able to engineer solutions to the analysis, management and manipulation of large data.
Rationale:
The introduction of a Bachelor of Science Degree will address a critical skills shortage in the country and will provide access for learners in South Africa to an advanced area of study in a critical contemporary discipline. This qualification in Data Science will ensure vertical articulation possibilities and further encourage the development of academic qualifications in this field. Learners with this qualification may expect to find work in a wide variety of positions, such as data scientists, software engineers, business analysts, and solutions architects. They will be able to work as researchers, statisticians, computer network professionals, network administrators, network analysts, software programmers, systems and intelligence analysts.
In addition, this qualification forms an important part of the evolving Academic Plan of the institution. The academic posture adopted by the institution has been to focus on the unique characteristics and needs of the general Northern Cape region in a manner that raises intellectual matters of local and global interest. The institution is keen to develop capacity for academic engagement in Data Science that is both wide in its reach and deep in the levels of intellectual competence. The qualification will provide access to learners in the Northern Cape to an advanced area of study in a critical contemporary discipline. Since there are considerable shortages in these skills and competences across the country, learners in possession of The Bachelor of Science in Data Science will thus be both employable and eligible for further study, at honours or a Postgraduate Diploma level.
Outcomes
- Develop an understanding and apply the basic physical principles as well as the basic statistical concepts.
- An understanding of the fundamental design, analysis, and implementation of basic data structures and algorithms, the analysis and evaluation of the data structure needs of particular problems, as well as gaining hands-on experience in the design, analysis, and implementation of C programmes by using basic data structures and algorithms.
- Have a theoretical background and understanding of how computer hardware functions and the competence to relate to his/her computer programme algorithm development and implementation of an efficient and optimal execution of the code in the hardware.
- Explore techniques of designing, analysing and implementing algorithms by using graph algorithms as a case study.
- An understanding of core aspects of IS, focusing on the knowledge, skills and processes involved in developing and/or acquiring information systems.
- A solid understanding of fundamental architectural techniques used to build high-performance processors and systems.
Assessment Criteria
Associated Assessment Criteria for Exit Level Outcome 1:
- Recognise essential factors in a physical system and the physical principles or processes involved.
- Define, interpret, and apply concepts and laws.
- Understand problems presented in verbal, numerical, or diagrammatic form and know how to proceed.
- Develop and execute a strategic problem-solving approach appropriate to each problem.
- Select and apply appropriate techniques, such as diagrams depicting key features of a problem.
- Formulate appropriate equations and perform mathematical solutions.
- Present numerical results with appropriate significant figures and units.
- Check working by orders of magnitude, physical reasoning, and dimensional analysis.
Associated Assessment Criteria for Exit Level Outcome 2:
- Apply advanced C programming techniques like pointers, dynamic memory allocation, and structures for problem-solving.
- Implement abstract data types such as linked lists, stacks, queues, and trees using C.
- Analyse, evaluate, and select appropriate abstract data types and algorithms for problem-solving.
- Apply fundamental building blocks of algorithms for developing solutions.
- Recall fundamental algorithms and transfer algorithmic methods to new problems.
- Analyse simple problems and construct algorithms for their solutions.
- Translate simple algorithms into working C programs and use an integrated development environment efficiently.
Associated Assessment Criteria for Exit Level Outcome 3:
- Identify the functional units of a basic computer.
- Translate statements expressed in natural language into formal descriptions using Boolean algebra.
- Perform binary arithmetic, construct truth tables, and design logic circuits.
- Analyse simple machine learning programs and trace the output.
Associated Assessment Criteria for Exit Level Outcome 4:
- Explain the "best", "expected", and "worst" case behavior of an algorithm.
- Identify characteristics of data and conditions leading to different behaviors in specific algorithms.
- Informally determine the time and space complexity of simple algorithms.
- List and contrast standard complexity classes.
- Conduct empirical studies to validate hypotheses about runtime derived from mathematical analysis.
Associated Assessment Criteria for Exit Level Outcome 5:
- Demonstrate an understanding of the Design and Implementation phases of the Systems Development Life Cycle.
- Design and implement an information systems project to specified requirements.
- Address project management issues surrounding an information systems project.
- Interact with and satisfy end users of an information system.
- Use a professional drawing tool to represent requirements and logical models.
- Design and implement databases using Microsoft SQL Server.
- Design the importance of report design in information systems.
Associated Assessment Criteria for Exit Level Outcome 6:
- Describe the overall machine architecture.
- Understand the design of a pipelined CPU and cache hierarchy.
- Analyse and evaluate CPU and memory hierarchy performance.
- Understand trade-offs in modern CPU design, including issues affecting superscalar and dynamically scheduled architectures.
- Describe a network and its components, differentiating between types of networks.
- Use different network parameters to model and solve network problems.
- Perform exchange of information/messages over a network using basic protocol commands.
- Understand the working mechanism of DNS and different variants of Reliable Data Transfer Protocols.
- Describe the working mechanism and differences of connection-less (UDP) and connection-oriented (TCP) transport layer protocols.
Integrated Assessment:
- Ensure credibility in assessment through clear and rigorous procedures aligned with fairness, validity, reliability, and practicability principles.
- Utilize integrated assessment extensively across the qualification, including in Work Integrated Learning.
- Conduct self and formative assessment through various methods in the face-to-face context.
- Integrate summative assessments at the end of constituent modules of the qualification.
Qualification Details
- Type
- National First Degree
- NQF Level
- 07
- Min. Credits
- 360
- SAQA Source
- More Information
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This page includes information from the South African Qualifications Authority (SAQA) . Builtneat Pty Ltd trading as Study Start, has modified all or some of this information. SAQA has not approved, endorsed, or tested these modifications.