Faculty of Postgraduate Studies
Postgraduate Programme
Level 7 Diploma in Data Science
The OTHM Level 7 Diploma in Data Science is a highly regarded postgraduate qualification designed to develop advanced skills and in-depth knowledge in key areas of data analytics and machine learning. It is equivalent to a Master’s level qualification (RQF Level 7) in the UK education framework and is ideal for professionals looking to progress in data analysis, business intelligence, AI development, and strategic data management roles.
This programme focuses on equipping learners with practical tools and strategic insights in machine learning, predictive analytics, big data processing, and data visualisation. Upon successful completion, learners can pursue further studies such as MSc Data Science (Top Up) to advance their professional career in technology-driven sectors across the globe.
The principal objective of the Level 7 Diploma in Data Science qualification is to develop the knowledge and skills and construct the means for extracting business-focused insights from data. This requires an understanding of how value and information flows in a business, and the ability to use that understanding to identify business opportunities. Learners will become competent and reflective practitioners, related to their current role, and in preparation for more challenging roles in the future.
Entry Requirements
- Applicants will have a minimum of two years management or supervisory experience AND
- Credit pass for English at the GCE O/L examination or equivalent
Duration
- 06 Months
Awarded by
Data science combines powerful computing technology, sophisticated statistical methods, and expert domain knowledge to analyse and gain practical insights from huge amounts of data produced by organisations at present business environment. The aim of this unit is to introduce a range of data science concepts, data administration and governance and big data sources.
The goal of this unit is to provide an overview of fundamental concepts in probability and statistics from first principles. This unit will introduce the core probability and statistical methods used in data science and a range of data analytic processes and techniques.
This unit will introduce you to some of the most widely used predictive modelling techniques and their core principles. Through this unit, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modelling.
This unit is essential for understanding the fundamentals of the data analysis process including gathering, cleaning, analysing and sharing data and communicating insights with the use of visualizations and dashboard tools. It is expected that students doing this unit will gain hands-on experience of implementing data analytic processes and techniques using a programming language such as Python, R, or a tool such as Weka, KNIME, PowerBI, Excel etc.
This unit is designed to introduce the science behind machine intelligence and the philosophical debate around the ambitions of simulating human intelligence to solve real-world problems. Students will be guided to appreciate AI types and applications and develop a better understanding of aspects related to intelligent agents. In this unit, students will master key concepts and gain the practical knowledge to apply machine learning principles to challenging real-world problems.
The aim of this unit is to develop learners’ ability to prepare for various types of academically based computing research through the development and design of a research proposal. Learners will develop a critical understanding of the philosophical, practical, and ethical concepts of research within the context of computing discipline.