Dates:
Healthcare Analytics:
17 Oct, 18 Oct, 20 Oct 2023 | 9am-5.30pm | Classroom Learning
Communicating Insights with Data Storytelling:
23 Nov, 24 Nov, 27 Nov 2023 | 9am – 5.30pm | Classroom Learning (Classes are fully booked)
28 Nov, 4 Dec, 8 Dec 2023 | 9am – 5.30pm | Classroom Learning
Duration: 6 Days
Course Objectives
This Professional Certificate will equip learners with the following competencies:
- Understand the importance of data to a healthcare institution for operations and planning, evaluation of performance goals and improvement of service and patient care.
- Learn the tools and techniques to clean, process, analyse and interpret various categories of healthcare analytics.
- Acquire analytic skills using the data analytics software.
- Understand and apply visualisation techniques and information displays to convey data and findings/
- Learn how to produce effective and efficient data visualisations.
- Present effective data storytellings.
Job Role Readiness
It will prepare learners in the following job roles to perform their responsibilities more effectively/ It will prepare learners for the following job roles:
- Data Analysts
- Health Informaticians
Programme Structure
Who Should Attend
- This programme is designed for mid-career PMETs and healthcare professionals who are looking to pivot into healthcare analytics roles.
- Health Informaticians
- Nurses
Prerequisites
At least a polytechnic diploma.
Course Conveners
(Click their photos to view their short biographies)
Dr Lek Hsiang Hui
Dr Lek Hsiang Hui
Dr Lek Hsiang Hui is a Specialist in Data Analytics, System Analysis and Development. He is an IT techie who is passionate about computer systems and technology.
He is involved in a few startups and is constantly looking into innovative IT solutions which can be translated to business ideas, with the recent one in the area of Big Data Analytics. He is also a mobile application developer and has produced more than 10 mobile apps.
Dr Lek has been teaching various undergraduate courses and executive courses in National University of Singapore (NUS) since 2006. Some of these modules include programming methodology, enterprise system analysis and development, and data mining. During this period, he has won a number of teaching awards such as NUS Annual Teaching Excellence Award (2015/16, 2016/17, 2017/18) and NUS Annual Teaching Excellence Honor Roll (2018/19), Faculty Teaching Excellence Award (2014/15, 2015/16, 2016/17), and Faculty Teaching Excellence Award Honor Roll (2017/18).
Dr Lek received his Doctor of Philosophy (Information Systems) from NUS in 2013. His research area is in Natural Language Processing (Sentiment Analysis). He graduated with a Bachelor’s Degree (1st class Honors) in Computer Engineering from NUS.
Industry Credentials
Shopping Malls (UOL, Marina Square, ION), Healthcare (SingHealth), Government (STB), various SMEs in F&B, Apparels, Cleaning Solutions, Photography, Health Products, Baby Products
Dr Yeo Wee Kiang
Dr Yeo Wee Kiang
Dr Yeo Wee Kiang is a Senior Lecturer at the Department of Information Systems and Analytics in the NUS School of Computing. Previously, Dr Yeo was Adjunct Lecturer at the Department of Economics in the NUS Faculty of Arts and Social Sciences. Since 2019, he has been teaching the ECA5372 Big Data Analytics module as part of the Master of Economics coursework programme. Additionally, he was a part-time lecturer at Nanyang Business School in Nanyang Technological University where he imparted knowledge on Python programming and analytics to undergraduate students pursuing business studies. Prior to these roles, Dr Yeo served as the Lead Instructor (Data Science Immersive) at a New York-based commercial Continuing Education and Training (CET) provider. In that capacity, he taught aspiring adult learners in Hong Kong, Sydney, and Singapore who were eager to upskill or transition into new careers. Dr Yeo received his doctorate from National University of Singapore. For his PhD work, he focused his research on machine learning and data mining within a multinational pharmaceutical company. His area of specialization involved developing computational methods aimed at uncovering potential medicinal drug candidates. He also holds the WSQ Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning Singapore.
Ms Samantha Sow
Ms Samantha Sow
Ms. Samantha Sow is currently a Senior Lecturer in the department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs). Prior to being an academia, Samantha worked in the research and development at Infineon Technologies. Her research and project areas include Business Analytics, Data Mining, Predictive and Prescriptive Analytics.
She has a passion for engaging and inspiring participants to enhance their workplace analytics capabilities and increase business intelligence quotient within their organisations. Her interests lie in the applications of data analytics, predictive modelling and optimization techniques to derive actionable insights for commercial effectiveness. She is familiar with typical analytics tools such as Python, R, and SAS, SPSS and Tableau. She also has working knowledge in the area of Analytics, Data Science and Machine Learning.
Samantha completed her Master of Education from University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours. She has also completed THEC (Teaching in Higher Education) and ACTA (Advanced Certificate in Training and Assessment). She is a member of the adult associate educator (AEN) by Institute for Adult Learning (IAL), Singapore.
Her certifications include:
Microsoft Certified Azure Data Scientist Associate. Microsoft Certified Data Analyst Associate. SAS Certified Predictive Modeller in SAS Enterprise Miner. Tableau Certified Desktop Specialist.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Codes
Healthcare Analytics: TGS-2022012279 (Classroom Learning) / TGS-2022012299 (Synchronous e-learning)
Communicating Insights with Data Storytelling: TGS-2022011489 (Classroom Learning) / TGS-2022011480 (Synchronous e-learning)