Overview
Building High-Demand Skills and New Capabilities for IR 4.0
The Master of Data Science programme at Help University Malaysia aims to produce graduates to meet the growing demand for data science professionals who are capable of making decisions based on the availability of comprehensive data. It prepares graduates to apply analytics techniques for knowledge discovery and dissemination to assist researchers or decision-makers in achieving organisational objectives.
Objectives
The objectives of the Master of Data Science are to produce graduates who are able to:
- Apply quantitative modelling and data analysis techniques to find solutions to real world business problems
- Communicate findings, and effectively present results using data visualisation techniques
- Recognise and analyse ethical issues in business related to intellectual property, data security, integrity, and privacy
- Demonstrate knowledge of statistical data analysis techniques utilised in decision-making.
- Use data mining software to solve real-world problems
- Employ cutting-edge tools and technologies to analyse Big Data
- Apply algorithms to build machine intelligence
- Demonstrate skills in teamwork, leadership and decision-making
Entry Requirements
- A Bachelor’s degree (Level 6, MQF) in Computing or related fields with a minimum CGPA of 2.50, as accepted by the HEP Senate; OR
- A Bachelor’s degree (Level 6, MQF) in Computing or related fields or equivalent with a minimum CGPA of 2.00 can be accepted subject to a minimum of FIVE (5) years of working experience in the related fields and rigorous internal assessment; OR
- Candidates without a qualification in the related fields or relevant working experience
- Achieve a minimum score of 6.0 in the IELTS or equivalent.
- If a student does not meet this requirement, the HEP must offer English proficiency courses to ensure that the student’s proficiency is sufficient to meet the needs of the programme.
Future Career
- Machine Learning Scientist
- Decision Analytics Manager
- Data Analytics Manager
- Data Scientist
- Data Innovation Manager
- Business Analyst Manager
- Business Intelligence Developer
- Data Architect
- Data Analyst
- Statistician
- Data Mining or Big Data Engineer
