Kickstarting Your Machine Learning Journey | SGInnovate


BASH, Level 3,
Block 79 Ayer Rajah Crescent via Lift Lobby 3
Singapore 139955

Kickstarting Your Machine Learning Journey

Organised by SGInnovate and NUS-ISS

Together with the National University of Singapore – Institute of Systems Science, SGInnovate is proud to bring to you an accelerated four-day Machine Learning workshop designed to kickstart your journey into this field. 

This workshop is designed for attendees with some technical skills i.e. software programmers, data analysts, developers who are comfortable with writing codes. Hit the ground running with hands-on Machine Learning experience through this workshop! 

Machine Learning is a field of research that can take years to attain mastery of it. Through this workshop, you will experiment in the areas that are most relevant today.  The goal is to help you construct a learning map of areas to continue improving on after each course. 

Machine Learning practitioners spend much time experimenting. This workshop will, therefore, focus less on mathematics and theory, and more on the practical aspects of getting started on experimentation. 

By the end of the course, you will be designing and implementing your project to apply what you learnt. 

To benefit most from this course, you are expected to have a basic programming background in Python, or are able to quickly self-learn Python along the way.

This workshop is eligible for funding support. For more details, please refer to the "Pricing" tab above.


  • Comfortable writing codes
  • Familiar with basic Python, NumPy and Pandas
  • Attendees MUST bring their laptops

In this course, participants will learn: 

  • How to describe the popular Machine Learning techniques and applications
  • To apply well-known Machine Learning models using Python libraries for classification, regression, and clustering
  • To implement the Machine Learning workflow (data preparation, feature engineering, training and validation) for supervised and unsupervised learning problems
  • To apply Machine Learning to a domain-specific problem of their choice, evaluate its effectiveness, and suggest further improvements

For enquiries, please send an email to

Day 1 (10 February 2020)

  • Introduction to Machine Learning
  • Application of NumPy in representing and manipulating data
  • Application of Pandas in transforming and querying data
  • Application of Matplotlib in data visualisation
  • Training your first Machine Learning model

Day 2 (11 February 2020)

  • Basics of training a Machine Learning model
  • Application of Machine Learning algorithms for data classification
  • Application of Machine Learning algorithms for data clustering
  • Going green: trees, forests for supervised learning

Day 3 (12 February 2020)

  • Coping with dimensionality
  • Individual project and checkpoint reviews

Day 4 (13 February 2020)

  • Individual project and checkpoint reviews
  • Individual project presentations

This is an intensive and compressed version of this 25-day course:

Funding Support

This workshop is eligible for CITREP+ funding.

CITREP+ is a programme under the TechSkills Accelerator (TeSA) – an initiative of SkillsFuture, driven by Infocomm Media Development Authority (IMDA).

*Please see the section below on ‘Guide for CITREP+ funding eligibility and self-application process’

Funding Amount: 

  • CITREP+ covers up to 90% of your nett payable course fee depending on eligibility for professionals

Please note: funding is capped at $3,000 per course application

  • CITREP+ covers up to 100% funding of your nett payable course fee for eligible students / full-time National Servicemen (NSF)

Please note: funding is capped at $2,500 per course application

Funding Eligibility: 

  • Singaporean / PR
  • Meets course admission criteria
  • Sponsoring organisation must be registered or incorporated in Singapore (only for individuals sponsored by organisations)

Please note: 

  • Employees of local government agencies and Institutes of Higher Learning (IHLs) will qualify for CITREP+ under the self-sponsored category
  • Sponsoring SMEs organisation who wish to apply for up to 90% funding support for course must meet SME status as defined here

Claim Conditions: 

  • Meet the minimum attendance (75%)
  • Complete and pass all assessments and / or projects

Guide for CITREP+ funding eligibility and self-application process:

For more information on CITREP+ eligibility criteria and application procedure, please click here

In partnership with:Driven by:


For enquiries, please send an email to

Lee Chuk Munn, Chief, StackUp Programme, NUS-ISS

Chuk Munn is with the Advanced Technology Applications Practice for the National University of Singapore, Institute of Systems Science (NUS-ISS). His current responsibilities include developing courseware, and teaching graduate and public courses in enterprise software engineering, software architecture, web technologies and enterprise Java.

Before joining NUS-ISS, Chuk worked for Oracle and Sun Microsystems where his primary responsibilities include helping customers and partners across all industries in the APAC region to develop, size and tune applications deployed to Java EE Application Servers.

Chuk has more than 20 years of working experience and more than 30 years of developing and debugging software.

His interest includes peer-to-peer networks, application frameworks, Java Virtual Machine and dynamic languages. He keeps himself busy by contributing to various open-source projects.

Topics: Artificial Intelligence / Deep Learning / Machine Learning / Robotics