Overview

In simple terms, Machine learning (ML) is the fusion of computer science and statistics in computer algorithms, and has become a key asset in today's technology. From shopper recommender systems to self-driving cars, ML has enabled intelligent solutions that go beyond the capabilities of traditional technological implementations.

ML is a concept that is most effectively learned by doing. The lessons will follow an active learning approach that includes group activities and gamified individual quizzes during the lessons. There will be a simple hands-on session at the end to expose attendees to the technicalities of ML implementations.

At the end of the 1.5-day course, you will be able to:

1. Understand the fundamental principles of ML
2. Appreciate the differences between the common types of ML like supervised and unsupervised learning
3. Know how ML is used in various applications like face detection and algorithmic trading
4. Use an online ML learning environment to solve some interesting problems

To aid companies in transforming their capabilities through their human capital, and support Singapore’s drive towards becoming a Smart Nation, this course is mapped to the Singapore Economic Development Board’s Singapore Smart Industry Readiness Index:

  • Dimension 10 - Shop Floor Intelligence
  • Dimension 11 - Enterprise Intelligence
  • Dimension 12 - Facility intelligence

Teaching Team

What You’ll Learn

Lesson 1: Getting to Know Machine Learning
  • What is Machine Learning?
  • Why does Machine Learning Matter?
  • Popular Applications of Machine Learning

Lesson 2: Types of Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforced Learning
  • Deep Learning

Lesson 3: Machine Learning in Action
  • Demonstration of Popular Machine Learning Applications
  • Demonstration using Python to Develop Machine Learning Applications

Lesson 4: Hands-on with Machine Learning
  • Coding Machine Learning Applications using Jupyter Notebooks in Colab
  • Drag and Drop "Programming" of an ML Prototype in the Python Programming Language

Who Should Attend

Working professionals in both ICT and non-ICT domains who are interested in getting an exposure to machine learning development.
 

SITizens Learning Credits (SLC) - Eligible Course

SIT Alumni: Before registering for courses, please activate your SITizens Learning Credits via the email sent by SIT Alumni Team, on behalf of SITLEARN Professional Development.

Registration Closed.


Prerequisites

 

Certificate and Assessment

A Certificate of Participation will be issued to participants who:
  • Attend 75% of the course, and
  • Undertake non-credit bearing assessment during the course.

Schedule

Day Date
Day 1   3 Aug 2020  
Day 2   11 Aug 2020 (9:00am to 1:00pm)

Fees

Category Full Fee After SF Funding After SF Mid-Career
Enhanced Subsidy
Singapore Citizen (Below 40) / Singapore PR $1,498.00 $449.40 Not Eligible
Singapore Citizen (40 & above) $1,498.00 $499.40 $169.40
Non-Singaporeans $1,498.00 Not Eligible Not Eligible

Note:
  • All figures include GST. GST applies to individuals and Singapore-registered companies.
  • You can opt for either SF Series Funding or Mid-Career Enhanced Subsidy. Both cannot be combined.

» Learn more about funding types available

Terms & Conditions:

SkillsFuture Funding

In order to be eligible for the 70% training grant awarded by SkillsFuture, applicants (and/or their sponsoring organisations where applicable) must:
  1.  Be a Singaporean Citizen or Singapore Permanent Resident
  2.  Not receive any other funding from government sources in respect of the actual grant disbursed for the programme

SkillsFuture Mid-Career Enhanced Subsidy

To be eligible for the 90% enhanced subsidy awarded, applicants (and/or their sponsoring organisations where applicable) must:
  1.  Be a Singaporean Citizen
  2.  Be at least 40 years old
  3.  Not receive any other funding from government sources in respect of the actual grant disbursed for the programme

SIT reserves the right to collect the balance of the programme fees (i.e. the potential grant amount) directly from the applicants (and/or their sponsoring organisations where applicable) should the above requirements not be fulfilled.

SIT reserves the right to make changes to published course information, including dates, times, venues, fees and instructors without prior notice.

Key Info

Venue SIT@Dover, 10 Dover Drive S138683
Time 09:00 AM to 06:00 PM
Date 03 Aug 2020 (Mon) to
11 Aug 2020 (Tue)
Registration is Closed.

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