Course Objectives
This Advanced Professional Certificate will equip learners with the following competencies:
- Learn what Business Analysis is & skillsets needed to be a Business Analyst.
- Learn data structures and programming constructs in Python and have a strong foundation in Python programming.
- Learn and apply the Python programming language for creating Machine Learning applications.
- Understand big data and how big data analytics can help organizations achieve a competitive advantage.
- Learn how to make strategic use of the data available in organizations.
- Learn how to communicate data insights through effective data storytelling.
Job Role Readiness
It will prepare learners in the following job roles to perform their responsibilities more effectively:
- Business Analyst
- Data Analyst
- Data Engineer
Who Should Attend
Professionals who plan to be a Data Analyst/ Business Analyst that is capable of integrating Business, Customer and Technology to produce digital products that the market needs.
Prerequisites
At least a polytechnic diploma (or equivalent)
Course Conveners
(Click their photos to view their short biographies)
Assoc Prof Danny Poo

Assoc Prof Danny Poo
Assoc Prof Danny Poo brings with him 35 years of Software Engineering and Information Technology and Management experience. A graduate from the University of Manchester Institute of Science and Technology (UMIST), England, Dr Poo is currently an Associate Professor at the Department of Information Systems and Analytics, National University of Singapore. Prior to joining the University, Dr Poo was with the System Operations at DBSBank, Singapore.
A Steering Committee member of the Asia-Pacific Software Engineering Conference, Dr Poo is actively involved in Information Management and Healthcare Analytics research. A well-known speaker in seminars, Dr Poo has conducted numerous in-house training and consultancy for organizations, both locally and regionally. Dr Poo is the author of 5 books on Object-Oriented Software Engineering, Java Programming language and Enterprise JavaBeans.
Dr Poo notable teaching credentials include:
- Data Strategy
- Data StoryTelling
- Data Visualisation
- Data Analytics
- Machine Learning
- Data Management
- Data Governance
- Data Architecture
- Capstone Projects for Business Analytics
- Software Engineering
- Server-side Systems Design and Development
- Information Technology Project Management
- Health Informatics
- Healthcare Analytics
- Health Informatics Leadership.
Industry Credentials
- Deutsche Bank
- Gemplus
- Micron
- NCR
- PIL
- PSA
- Rhode-Schwarz
- Standard Chartered Bank
- ST Electronic
- Monetary Authority of Singapore
- Infocomm Development Authority
- National Library Board
- Ministry of Manpower
- Nanyang Technological University
- Nanyang Polytechnic
- National University Hospital.
Dr Ai Xin

Dr Ai Xin
Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience on teaching Artificial Intelligence and Data Science courses, e.g. machine learning, deep learning, data mining and etc.
She graduated from NUS with a PhD degree on Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks.
She worked in BHP Billiton Marketing Asia for eight years and gained a lot of industry experience through different functions, e.g. risk management, supply chain management, sales and marketing planning and etc.
Dr Amirhassan Monajemi

Dr Amirhassan Monajemi
Dr Amirhassan Monajemi is a Senior Lecturer in AI and Machine Learning with the School of Computing (SoC) at the National University of Singapore (NUS). Prior to SoC, he was a Senior Lecturer in NUS School of Continuing and Lifelong Education (SCALE) teaching AI and Data Science to adult learners. Before joining the NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science. He was born in Isfahan, Iran. He studied towards BSc and MSc in Computer Engineering at Isfahan University of Technology (IUT), and Shiraz University respectively. He got his PhD in computer engineering, pattern recognition and image processing, from the University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Learning, Machine Vision, IoT, Data Science, and their applications.
He has taught the artificial intelligence courses, including AI, Advanced AI, Expert Systems, Decision Support Systems, Neural Networks, and Cognitive Science since 2005 at both undergraduate and postgraduate levels. He was awarded the best university teacher of the province in 2012. He also has studied Learning Management Systems, E-Learning, and E-Learning for workplaces since 2007.
Dr Monajemi has registered a few patents in the fields of AI, Machine Vision, and Signal Processing applications, including an AI and machine vision-based driver drowsiness detection system and a low power consuming spherical robot. He also has published more than a hundred research papers in peer-reviewed, indexed journals and international conferences (IEEE, Elsevier, Springer, and so on), and supervised several Data Science, IoT, and AI industrial projects in various scales, including Isfahan intelligent traffic system delivery and testing, and red light runners detection. He is experienced in different sub-domains of Artificial Intelligence and Machine Learning, from theory to practice, including Deep Learning, Logic, and Optimisation.
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.
Training Roadmap
Stage 1: Professional Certificate in Digital Business Analysis
Curriculum:
- Business Analysis Planning and Strategy Analysis
- Requirement Modeling and Digital Solution Design
- Digital Solutioning and Delivery
Stage 2 (with Stage 1 as prerequisite): Professional Certificate in Machine Learning Using Python
Curriculum:
Stage 3 (with Stage 1 and 2 as prerequisites): Professional Certificate in Data Strategy and Storytelling
Curriculum:
Stage 4 (with Stage 1 to 3 as prerequisites): Advanced Professional Certificate in Business Analytics
Completion of Stage 1 to 3 curriculum earns the participant an Advanced Professional Certificate in this programme
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
Catalogue of Programmes for Individuals
- Course Category
- Artificial Intelligence & Machine Learning
- Business Analytics & Data Science
- Cloud Computing & Internet of Things
- Cybersecurity & Data Governance
- Digital Business & Technopreneurship
- Digital Health & Nursing Informatics
- Digital Technology & Innovation Management
- Digital Transformation & Change Leadership
- Education Technology & Learning Design
- Emerging & Disruptive Technologies
- FinTech & Blockchain
- Interactive Media Development & Metaverse
- Software Programming & Networking
- UX/UI Design & Digital Product Management