Higher Diploma in Science in Data Analytics

Program Overview

The Higher Diploma in Science in Data Analytics is a two-year part-time program that equips learners with the technical and design skills required for a career in Data Analytics. The program covers topics such as web and business application, predictive modeling, statistics, programming, machine learning, and advanced visualization. Graduates are well-positioned for careers as Senior Data Analysts, Data Engineering and Analytics, Financial Analysts, and more.

Program Outline

Higher Diploma in Science in Data Analytics | Part-time

Degree Overview:

Objective:

• Develop critical thinking skills to analyze industry trends in Big Data.
• Equip learners with the technical and design skills required by industry and deepen knowledge of statistical analysis and analytical models.
• Enable learners to implement scalable Big Data applications.
• Prepare learners to work effectively and collaboratively.
• Provide work opportunities to apply knowledge to real-world situations.

Program Description:

This two-year part-time program provides learners with the necessary knowledge and skills to become ICT/Data Analytical practitioners in various commercial, industrial, and public sector environments. The program focuses on the theory and practice of Data Analytics, covering topics like web and business application, predictive modeling, statistics, programming, machine learning, and advanced visualization. Learners will gain hands-on experience using various tools and techniques to generate actionable insights for stakeholders and support strategic decision-making.

Outline:

Content:

• The program covers the following modules:
• Advanced Analytics and Web Application
• Applied Data Analytics
• Big Data Managing and Processing
• Data and Network Mining
• Data Visualisation & Communications
• Databases for Business Applications
• Platforms for Data Analytics
• Programming for Data Analytics
• Project
• Statistics for Data Analytics

Structure:

• The program is divided into two semesters, with the first semester focusing on foundational modules and the second semester covering advanced modules.
• Semester one modules include:
• Advanced Analytics and Web Application
• Programming for Data Analytics
• Statistics for Data Analytics
• Databases for Business Applications
• Semester two modules include:
• Applied Data Analytics
• Big Data Managing and Processing
• Data and Network Mining
• Data Visualisation & Communications
• Platforms for Data Analytics
• Project (choice of Placement or Project)

Modules:

• Each module is designed to provide learners with specific knowledge and skills in a particular area of Data Analytics.
• The modules are delivered through a variety of learning approaches, including face-to-face, live online, recorded online, and directed e-learning.

Assessment:

• The program employs a combination of assessment methods to evaluate learners' knowledge and skills.
• These methods include:
• Take-home assignments
• Skills-based assessments
• Practical lab tasks
• Projects
• Demonstrations
• Presentations
• Conventional examinations

Teaching:

• The program is delivered by experienced faculty with expertise in Data Analytics and related fields.
• The teaching approaches are designed to be interactive and engaging, with a focus on practical application of knowledge.
• The program also utilizes a variety of learning resources, including online materials, software, and datasets.

Careers:

• Graduates of the program are well-positioned for careers in the growing field of Data Analytics.
• Potential job titles include:
• Senior Data Analyst
• Data Engineering and Analytics
• Financial Analyst
• Power BI Data Analyst
• Consulting: Data Analyst
• Lead Business Analyst

Other:

• The Higher Diploma in Science in Data Analytics is a recognized qualification that is valued by employers in the ICT sector.
• The program is also eligible for funding under the Springboard+ initiative.

Note:

Please refer to the program website for the most up-to-date information regarding fees, admission requirements, and application procedures.