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Graduate Diploma in Analytics and Visualisation

Graduate Diploma

To offer training in data visualisation, data wrangling and machine learning for a career in data analytics and data science.

Graduate Diploma in Analytics and Visualisation


Register for our programme briefing session at the SUSS e-Open House on 31 Aug 2024 (Sat) to have your queries answered by our faculty. You can also watch our programme briefing video at your own time and attend enrichment talks by industry experts.

[ Register now! ]

The business world is increasingly reliant on data-driven decision-making and insights. What was once the domain of statisticians and computer scientists is now a critical skillset for business executives who can use data to transform their organizations at an unprecedented pace.

The Graduate Diploma in Analytics and Visualisation (GDAV) programme offers a comprehensive curriculum that will enable you to become proficient in leading-edge tools such as R, Python, MySQL, and SPSS Modeler for data visualisation, wrangling, and analytics-driven decision-making. You will also learn open-source and enterprise tools in automation, allowing you to streamline data and workflow processes and deliver powerful business solutions.

By completing the GDAV programme, you will acquire practical skills for a data-related role and gain valuable intuition in translating and addressing business problems using methods in data analytics, which are increasingly important in today’s data-driven organizations.

What our students say:


As a post-grad student, I found the GDAV programme to be well-structured and very enriching. The curriculum is well-calibrated and many of the modules contain real-life practical applications.

To this end, kudos to all the lecturers for being very patient and professional. All these helped with my learning journey as well as allowing me to confidently apply the knowledge gleaned from the course to the workplace. I fully recommend the GDAV!

Marcus Lee, GDAV ‘22

Getting started on a new skill is never easy. Despite that, the professors in the GDAV course were very patient and knowledgeable while sharing their real-life experiences.

I was able to pick up many new skills for data analytics using R, Python, MySQL, even automation tools such as ServiceNow and UiPath, which would definitely be put to use in my workplace.

Norine Liana Juri, GDAV ‘23

Unique Features of the Programme

  • The programme is designed with a strong industry focus, providing you with practical skills and knowledge that can be immediately applied in a data-related work environment.
  • You will learn how to use a range of leading-edge tools in data analytics tools such as R, Python, MySQL, and SPSS, as well as open-source automation tools like UiPath and enterprise-grade platforms for workflow automation.
  • You will become competent in completing various tasks in an analytics workflow, from data visualisation, data wrangling and machine learning, and gain valuable skills in translating business problems into actionable tasks that can be addressed with data analytics methods.
    As part of the programme, you will have the opportunity to complete an applied project in a structured learning environment, closely guided by both an industry or academic mentor, to help prepare you for a data-related role in the industry.
  • The courses are designed to be self-contained, and no prior knowledge of analytics or programming is assumed.

Admission Requirements

Refer to general admission criteria for graduate programmes.

This programme is currently unable to take in international students, i.e., you must be a Singapore citizen, permanent resident or a resident in Singapore (e.g., Employment Pass holder) in order to apply for admission.

Applicants will be required to submit a CV detailing their relevant experience (education, training and/or work). Applicants are also encouraged (not mandated) to include the contact information (email address and/or phone number) of at least one referee.

Financial Assistance

The University offers course fee concession for selected graduate programmes. Please click here for more details.

Programme Structure

GDAV students are required to complete 30 credit units (cu) of coursework. However, they can also opt to exit with the Graduate Certificate in Analytics and Visualisation (GCAV) upon completion of 15 cu of courses. Courses are based on a 5-cu configuration unless stated otherwise. The candidature for GDAV has a minimum period of one (1) year and a maximum period of two (2) years. Classes are conducted in the evenings during weekdays, so students can continue to work in the day and study in the evening.


The GDAV programme is designed for individuals who are interested in gaining skills in connecting business, data, and IT, and developing competence in working with data, designing analytics solutions, and creating visualisations with valuable business insights. The programme is ideal for management staff in organisations that generate large amounts of data, as well as professionals seeking career advancement in data-related roles, such as data analysts, business intelligence analysts, and automation solutions architects.

Previous students of the programme have come from diverse industries including the public sector, healthcare, human resources, finance, education, and marketing, highlighting the relevance and applicability of the programme across a wide range of industries.

The GDAV programme provides a strong foundation for pursuing diverse data-related roles across different industries. Graduates of the programme can explore careers in positions such as data analysts, business analysts, analytics and automation solutions architects, and managerial roles responsible for driving data and automation initiatives within an organization.
  1. What does the applied project involve?

    ANL588 Applied Project is a project-based course where students will complete an analytics or automation project under closed supervision of an industry or academic mentor. The course focuses on preparing students for the job market, which consists of project mentoring sessions, seminars on machine learning and computing, and activities for job preparation. You may take ANL588 Applied Project after completing at least 15cu of courses from the programme, of which, you must have completed ANL501 Data Visualisation and Storytelling, ANL503 Data Wrangling.

  2. When are the lessons scheduled?
    Lessons are scheduled on one to two weekday evenings per week from 7pm to 10pm.

  3. What are the assessment components in each course?
    It consists a mixture of pre-course quiz, participation, group-based assignments and End of Course Assessments

  4. What happens if I do not complete the graduate programmes (e.g. Graduate Certificate, Graduate Diploma, Master) within the candidature period? Can I apply to take the remaining courses via CET pathway?
    Students who have not completed their graduate programmes within the stipulated candidature period will not be eligible for the award of the qualification for such graduate programmes. Such students however may apply to take, via the CET pathway, the remaining courses which they did not complete under their graduate programmes as part of their personal learning and development. Such application will be subjected to the CET admission requirement. However, as such students have exceeded the candidature period for their graduate programmes, they will not be awarded the qualification for such graduate programmes even after taking and completing the remaining courses via the CET pathway (“Condition”).

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