Advanced Manufacturing Centre

About Us

The Advanced Manufacturing Centre (AMC) aims to provide consultancy projects for companies, particularly for SMEs, in adopting Advanced Manufacturing technologies. AMC will help companies adopt technologies where automation, robotics and big data will bring manufacturing to the next level. The centre will work closely with the schools and PACE to offer skills training to technology adopters and learning journeys for industry.

Contact Us

Get connected with Advanced Manufacturing Centre (AMC) at enterprise@sp.edu.sg.

Building Information Modelling Centre

About Us

The Building Information Modelling Centre (BIMC) aims to be a platform to progress learning, integrative research and upgrading training in the Built Environment industry. It serves as part of the building industry catalyst to drive towards supporting the digital technological adoption to shape and transform collaboration, productivity, and innovation across the different genres of the professional building disciplines.

Vision & Mission

Vision

A regional centre for learning, research and collaboration in BIM innovation and integration across disciplines and genres in the built environment.

Mission

To support and facilitate learning, research and collaboration in BIM innovation and integration.

  • Provide rigorous and current training in BIM digital adoption and integration in the built environment industry.
  • Cross-disciplinary research driving productivity and effective collaborations among the professional genres and consultancies of the building industry.
  • Inspire BIM innovation through facilitating SMART and digital solutions.
Contact Us

Get connected with Building Information Modelling Centre (BIMC) at enterprise@sp.edu.sg.

Business Innovation Centre

About Us

The Business Innovation Centre (BIC) will focus on creating value-exchange with industry in the ITM Lifestyle cluster (food services, manufacturing, retail and hotel) in the following areas:

  • Regionalisation – helping companies to venture overseas
  • Human Resource – helping companies to strengthen HR practices
  • Applied Industry Projects and Proof-Of-Concept – helping companies to create new ideas
Contact Us

Get connected with Business Innovation Centre (BIC) at enterprise@sp.edu.sg.

Data Science and Analytics Centre

About Us

The Data Science and Analytics Centre (DSAC) will partner industry in Data Science and Analytics (DSA) projects through:

  • Innovation – harnessing data and applying DSA techniques to derive business insights through applied research;
  • Solutioning – developing data products; and
  • Training – building employees’ capability to practise DSA at the workplace.
Vision & Mission

Vision: A leading centre in applied data science and analytics for innovation, solutioning and training.

Mission: To support SkillsFuture and Industry Transformation across sectors through

  1. Building strong DSA capabilities in our students and professionals
  2. Strengthening enterprise capabilities in DSA to improve productivity
  3. Partnering industries to enable innovation and growth
The Team

Dr. Edna Chan (Centre Director)

Research Interest: Data Analytics, Learning Analytics, Machine Learning, Optimization, Text Analytics

Dr. Edna Chan (Centre Director)

Research Interest: Data Analytics, Learning Analytics, Machine Learning, Optimization, Text Analytics

Dr. Edna is an enthusiastic teacher, researcher and developer. She received the Outstanding Graduate Teaching Assistant award in 2002 while working on her Ph.D., and the Excellence in Teaching award in 2009 at SP. National funding sources she has received include MOE Innovation Fund, and MTI-MOF Public-Private Co-Innovation Fund. Her latest research which involves the development of the Learning Analytics Networked Tutoring System (LearningANTS), a research collaboration between SP and 3ELogic, received the MOE Innergy SB Award in 2016. She is a member of Phi Kappa Phi, Golden Key and Omega Rho.

Ms. Dora Chua

Research Interest: Internet Of Things (IoT), Big Data Platforms (Hadoop), Streaming Analytics (Spark), Cognitive Services (Image Recognition/ Chatbots), cloud computing platforms (AWS, Azure, Google Cloud)

Ms. Dora Chua

Research Interest: Internet Of Things (IoT), Big Data Platforms (Hadoop), Streaming Analytics (Spark), Cognitive Services (Image Recognition/ Chatbots), cloud computing platforms (AWS, Azure, Google Cloud)

Ms. Dora has a breadth of experience in developing desktop, web-based and mobile applications using various programming languages such as C#, Java, PHP, Python, JavaScript, C++ etc. Besides her strength in application development, she is also proficient in other areas such as database design/ administration, user interface design and data visualization. She was awarded with the Accenture Gold Medal as the top student in her Master degree course with the Institute of System Science (ISS) at NUS in 2011. Ms. Dora is a certified Amazon Web Services (AWS) trainer.

Ms. Leong Fong Sow

Research Interest: Machine Learning, Software Engineering, Internet Computing, Curriculum Design

Ms. Leong Fong Sow

Research Interest: Machine Learning, Software Engineering, Internet Computing, Curriculum Design

Ms. Leong is a keen software developer and an experienced educator with a demonstrated history of working in the higher education industry. She is skilled in Curriculum Development and Web/Mobile Application Development. She had served as the Chairperson of the course management team of the Diploma in Business Information Technology and Diploma in Information Technology offered by Singapore Polytechnic.

Dr. Peter Leong

Research Interest: Artificial Intelligence, Machine Learning, Big Data, Internet of Things, Cloud Computing

Dr. Peter Leong

Research Interest: Artificial Intelligence, Machine Learning, Big Data, Internet of Things, Cloud Computing

Dr. Leong is an experienced technopreneur in high-tech hardware and software technology companies. He is always keen to take advantage of new emerging technologies to improve lives and add economic value. He has played varied roles in his high-tech career as Researcher, Academic, Project Manager, Software Architect, and Software Developer in a wide variety of Internet, ubiquitous and mobile applications.

Dr. Robert Straughan

Research Interest: Data Mining, Text Analytics, Optimization

Dr. Robert Straughan

Research Interest: Data Mining, Text Analytics, Optimization

Dr. Straughan worked for several years in the U.S. as a chemical engineer in the Oil & Gas Industry before receiving his Ph.D. in Applied Mathematics. After relocating to Singapore, he worked at a Japanese MNC where he developed mathematical libraries for vector supercomputers, and at a research institute where he led a team that carried out commercial data mining projects. As a Senior Lecturer at SP, he teaches statistics and data mining, and leads data analytics projects. He is the course chair of the Specialist Diploma in Data Science (Data Analytics).

Dr. Jaya Shreeram

Research Interest: Statistical Modelling / Predictive Analytics Theory, System Quality and Reliability by Statistical Design

Dr. Jaya Shreeram

Research Interest: Statistical Modelling / Predictive Analytics Theory, System Quality and Reliability by Statistical Design

Dr. Jaya received his PhD in Industrial and Systems Engineering. His research interests include Statistical Modelling and Predictive Analytics theory. He has supervised several postgraduate research work and has published in the area of System Quality and Reliability by Statistical Design. He has a record of teaching and working in the higher education industry. He is currently a Senior Lecturer at Singapore Polytechnic where he teaches Mathematics, Statistics and Data Analytics and is the Course Chair of the Specialist Diploma in Data Science (Predictive Analytics) program offered by Singapore Polytechnic.

Expertise

Data Visualization

Data visualization is used to help understand the organization’s data by translating it into more visual representations with interactivity.

Data Visualization

Data is everywhere in modern organizations. We have production data, human capital data, e-commerce data, transactions data, and yet the abundance of data often challenges organizations to make sense of it and extract value from it. Data visualization is used to help understand the organization’s data by translating it into more visual representations with interactivity.

  • Interactive dashboards (e.g. Tableau)
  • Using Power BI and Excel for Business Intelligence
  • Data Storytelling with Excel

Streaming Analytics

Streaming analytics is used to derive insights and predictions from streaming data.

Streaming Analytics

The advent of robust technology for storing, processing and distributing large amount of data (namely cloud and big data) made possible innovative new businesses such as Uber and Mobike. Operational data is often in the form of streaming
data and a large percentage of the data is unstructured data. Streaming analytics is used to derive insights and predictions from streaming data.

  • Analysis of unstructured Big Data
  • Analysis of streaming Big Data
  • Data Lake implementation

Machine Learning

Machine learning algorithms make it possible for a computer to improve its performance at a task by learning from large amounts of data passed to it.

Machine Learning

Machine learning algorithms make it possible for a computer to improve its performance at a task by learning from large amounts of data passed to it. In a data-rich organization, machine learning help improve efficiency by enabling the automatic processing of data to extract key trends and parameters.

  • Deep Learning for text processing
  • Deep Learning for image processing
  • Intelligent chatbots and software agents

Data Analytics

Data Analytics is the process of deriving insights from data in order to make better decisions.

Data Analytics

Almost all organisations have data, whether it is customer data, transaction data, or manufacturing data. This data often contains hidden information that is valuable to the organization. Data Analytics is the process of deriving insights from data in order to make better decisions. The Data Analytics process starts with a business objective, and entails the selection, transformation, and modelling of data. The models that result and aid in decision-making range from interactive charts and tables to advanced predictive models.

  • Customer churn analysis
  • Market basket analysis
  • Customer segmentation

Predictive Analytics

Predictive Analytics is used to predict future events or unknown outcomes.

Predictive Analytics

While Descriptive Analytics tells us what has happened in the past, Predictive Analytics is used to predict future events or unknown outcomes. When is equipment failure likely to occur? Which credit card transactions are likely to be fraudulent? Which customers are likely to respond to an offer for a new product? Predictive Analytics uses both advanced statistical modelling and machine learning to answer these questions.

  • Predictive maintenance
  • Credit risk analysis
  • Inventory management

Text Analytics

Text Analytics makes it possible to summarize and visualize patterns within text, cluster documents according to topics, and extract and prioritize recurring customer concerns found in text data.

Text Analytics

Much of the useful information organizations own is contained in unstructured text. Without automated techniques, it is difficult or impossible to find useful patterns in large volumes of text. Among other things, Text Analytics makes it possible to summarize and visualize patterns within text, cluster documents according to topics, and extract and prioritize recurring customer concerns found in text data.

  • Analyse call centre logs and customer forums
  • Use text data as inputs to predictive models
  • Retrieve information from collections of documents

Optimization

Representing these systems by mathematical models allows optimization algorithms to find optimal solutions that maximise revenue, minimise costs, or improve efficiency.

Optimization

Complex systems such as logistics networks, telecommunication networks, and manufacturing plants cannot be operated efficiently using human judgement alone. Representing these systems by mathematical models allows optimization algorithms to find optimal solutions that maximise revenue, minimise costs, or improve efficiency. These techniques are used across many industries from agriculture to finance.

  • Airline fleet routing and assignment
  • Oil refinery optimization
  • Optimization of energy systems
Training

Nurturing the critical skillsets Data Analytics through Structured training

Our Specialist Diploma programs and short courses offer well structured, rigorous learning platforms for anyone who needs to apply essential Data Analytics skills in their current job, and prepares one to enter a career in Data Science.

Nurturing the critical skillsets Data Analytics through Structured training

Data Analytics was identified as one of the eight priority areas and emerging skills required across different sectors during the launch of the New SkillsFuture Series on 28 Oct 2017.

‘Artificial Intelligence and Data Analytics’ was outlined as one of the four frontier technologies that for the development of Singapore’s digital economy during the Industry Transformation Map for the Infocomm Media sector on 3 Nov 2017.

Our Specialist Diploma programs and short courses offer well structured, rigorous learning platforms for anyone who needs to apply essential Data Analytics skills in their current job, and prepares one to enter a career in Data Science.

Specialist Diploma in Data Science - Not One but Four!

We offer four Specialist diploma in Data Science that are designed to first equip students with fundamental of statistics and programming skills before advancing to modules that deepen data skills that span across the Data Science pipeline.

Specialist Diploma in Data Science - Not One but Four!

Data Science is inherently a discipline that straddles between Computer Science and Mathematics.

We offer four Specialist diploma in Data Science that are designed to first equip students with fundamental of statistics and programming skills before advancing to modules that deepen data skills that span across the Data Science pipeline.

What is Data Science pipeline? It is the sequence of events that happen when we conduct a data science project, starting from data engineering to descriptive analytics, follow by predictive analytics, and finally prescriptive analytics.


Our four specialist diploma programmes to provide specialized training in these areas as listed below:

Specialist Diploma in Data Science (Data Analytics), SDDS (DA)
Specialist Diploma in Data Science (Predictive Analytics), SDDS (PA)
Specialist Diploma in Data Science (Artificial Intelligence), SDDS (AI)
Specialist Diploma in Data Science (Big Data & Streaming Analytics), SDDS (BDSA)

Data Analytics Skills Series

Critical skillsets in Data Science include data visualization, quantitative strategies for data analysis, predictive modelling and risk evaluation, computational strategies to simulate system behaviour and building software agents to learn, improve, adapt and produce desired outcomes or task.

Data Analytics Skills Series

“Courses for anyone who wants to integrate Data Science to their daily job.”

We offer Data Analytics short courses, designed to impart essential skillsets in Data Science!

Critical skillsets in Data Science include data visualization, quantitative strategies for data analysis, predictive modelling and risk evaluation, computational strategies to simulate system behaviour and building software agents to learn, improve, adapt and produce desired outcomes or task.

Programme Level Description
Fundamental of Analysis using Excel, 2 Days Beginner Designed to equip participants with relevant Excel skills for analysing data in business applications.
Data Visualization with Tableau, 2 Days Beginner Designed to equip participants with skills to create interactive visualizations and dashboards for presentation.
Data Visualization using Python, 2 Days Beginner Designed to equip participants with essential knowledge on data visualization through Python programming.
Introduction to AI & Machine Learning, 1 Day Beginner Designed to introduce artificial intelligence (AI) and machine learning (ML)to solve real-life problems.
Contact Us

Get connected with Data Science and Analytics Centre (DSAC) at enterprise@sp.edu.sg.

Energy and Chemicals Training Centre

About Us

The Energy and Chemicals Training Centre (ECTC) will drive and sustain business development in the following key industry areas: Energy and Chemicals (E&C), Specialty Chemicals, Biologics and Pharmaceuticals, and Consumer Chemicals, focusing on training programmes (PET & CET) identified by the Skills Framework for E&C, applications and R&D, and special projects such as co-location of training facilities, digitalisation, etc.

Contact Us

Get connected with Energy and Chemicals Training Centre (ECTC) at enterprise@sp.edu.sg.