Deep Learning Jump-Start Workshop | SGInnovate
April 14-24


BASH, Level 3, 79 Ayer Rajah Crescent
Singapore 139955

Deep Learning Jump-Start Workshop

Presented by SGInnovate

SGInnovate partners with Red Dragon AI to offer hands-on, cutting-edge training to developers and data scientists who are looking to build AI Applications for real world use.

This workshop gives participants a grounded understanding of how Deep Learning works and how to start applying it straight away for their own unique projects.


The workshop consists of a full day session on 14th Apr (Sat), with 2 follow-up sessions on the evenings of 17th Apr (Tue) and 24th Apr (Tue) and is eligible for funding support.


Attendees MUST bring their own laptops


Workshop Overview:
In the course participants will learn:

  • The basic concepts of Neural Networks and an introduction to the mathematics of Deep Learning
  • Introduction to the Keras API and how it works as a higher level of abstraction for TensorFlow
  • Building and using TensorFlow native Estimators
  • Building various types of Deep Learning models
  • Building models for Computer Vision challenges
  • Building models for Natural language challenges

The course will consist of a full day on 14th Apr (Sat) from 8:45am to 5:30pm with lunch and 2 tea breaks provided.

At the end of the day, once participants have an understanding of the basics, they will go home to work on their own models and projects.

There will then be 2 follow up evenings on 17th Apr (Tue) and 24th Apr (Tue) that will look at more advanced uses of Deep Learning for Computer Vision and for Natural Language Processing and allow for students to ask questions about their own projects.


Recommended Prerequisites:

  • An interest in Deep Learning
  • Ability to be able to read and follow code
  • We will send out some videos to help people with Python syntax specifically before the course begins.



Day 1, 14th Apr (Saturday)

08:45 Registration

09:15 The Key Concepts behind Deep Learning and Introduction to the basic math

10:45 Tea Break

11:00 Building your first Neural Network

12:30 Lunch

13:30 Building a Convolutional Neural Network

15:00 Tea Break

15:15 Using Transfer Learning for new problems

16:15 Doing a Project

17:15 Closing Comments and Questions


Evening Follow up Session 1, 17th Apr (Tue)

18:45 Registration

19:00 Deep Learning for Natural Language Processing Evening Session

21:00 Project Clinic 1

21:30 Closing Comments and Questions


Evening Follow up Session 2, 24th Apr (Tue) 

18:45 Registration

19:00 Deep Learning for Computer Vision Evening Session

20:00 Building a Model for Structured Data with TensorFlow Estimators

21:00 Project Clinic 2

21:30 Closing Comments and Questions


Day 1, Section 1: The Key Concepts behind Deep Learning and Introduction to the basic math

A simple introduction to how the math behind networks works

  • Math of Neural Networks and Back Propagation
  • Activation functions
  • Loss functions
  • Optimization functions


Day 1, Section 2: Building your first Neural Network

Frameworks: TensorFlow, Keras

A look into the Keras API

  • Parts of a Model
  • Hidden Layers in action
  • Keras Layers API
  • Multi-Layer Perceptrons
  • Setting Hyperparamaters


Day 1, Section 3: Building a Convolutional Neural Network

Frameworks: TensorFlow, Keras

Convolutional Model Architectures

  • Convolution layers
  • Pooling layers
  • Dropout and how it affects networks
  • Combining Convolution layers


Day 1, Section 4: Using Transfer Learning for new problems

Frameworks: TensorFlow, Keras

Understanding the Estimator framework and its advantages

  • Inception Network
  • Building a classifier with a pre-trained network
  • Reusing and retraining weights for a specific task


Day 1, Section 5: Doing a Project

Frameworks: TensorFlow, Keras

Actually *doing something* is very important

  • Ideas for projects to do
  • Q&A on ‘doable projects’
  • Homework: What to bring to the next session


Evening Follow up Session 1, Section 6: Deep Learning for Natural Language Processing Evening Session

Frameworks: TensorFlow, Keras, Estimators

Using Deep Learning for problems related to language

  • Ways to represent words and language
  • Intro to RNNs
  • Classifying Text
  • Project questions and general follow up


Evening Follow up Session 1, Project Clinic 1


Evening Follow up Session 2, Section 7: Deep Learning for Computer Vision Evening Session

Frameworks: TensorFlow, Keras, Estimators

Various types of Computer vision tasks

  • Understanding more advance image networks
  • Generative modeling for images
  • Examples of Style Transfer and Deep Dream


Evening Follow up Session 2, Section 8: Building a Model for Structured Data with TensorFlow Estimators

Frameworks: TensorFlow, Estimators, Datasets API

Understanding the Estimator framework and its advantages

  • What makes up an Estimator
  • Canned Estimator
  • Building a network for Structured Data
  • Estimator Input function
  • Intro to the TensorFlow Datasets API


Evening Follow up Session 2, Project Clinic 2


Instructors’ Biodata:

Dr Martin Andrews

Martin has over 20 years of experience in Machine Learning and using it to solve problems in financial modeling and creating AI automation for companies. His current area of focus and specialty is in Natural Language Processing and understanding. In 2017 Google appointed Martin one of the first 12 Google Developer Experts for Machine Learning.


Sam Witteveen

Sam has used Machine Learning and Deep Learning in building multiple tech startups, including a children’s educational app provider which has over 4 million users worldwide. His current focus is AI for conversational agents to allow humans to interact easier and faster with computers. In 2017 Google appointed Sam one of the first 12 Google Developer Experts for Machine Learning in the world.




Attendees Pre-Workshop Instructions

1) You MUST bring your own laptop to this workshop.

2) Please watch the introductory videos we will send out separately.

3) Please experiment with the pre-exercises given as well.


Funding Support

This workshop is eligible for e2i and UTAP Funding Support schemes.



An initiative of the National Trades Union Congress (NTUC), e2i (Employment and Employability Institute) supports nation-wide manpower and skills upgrading programmes.


Criteria for e2i Funding Support eligibility:

  • Participant must be a Singaporean or a Singapore Permanent Resident
  • Company-sponsored participant must not be from a Public Agency (includes but not limited to Ministries, Statutory Boards, Organisation of State, etc)
  • Achieves 100% workshop attendance
  • Must complete & submit a survey form after the online registration to fulfill funding requirements

* Note: e2i Funding is on a reimbursement basis and processing of the refund may take up to 2 months after course completion. Participants who do not fulfill ANY of the above criteria will NOT be eligible for e2i funding.



Union Training Assistance Programme (UTAP) is an individual skill upgrading account for NTUC members. As a member, you will enjoy UTAP funding up to 50% of the unfunded^ course fee, capped at $250 every year.

(^Unfunded course fee refers to the balance course fee payable after applicable government subsidy. This excludes GST, registration fees, misc. fees etc.)


Criteria for UTAP Funding Support eligibility:

  • Participant must have paid-up union membership before course commencement, throughout whole course duration and at the point of claim
  • The course must not be funded through company sponsorship or other types of funding
  • Achieves 100% workshop attendance
  • UTAP self-application must be submitted within 6 months after course completion

* Note: UTAP Funding is on a reimbursement basis and processing of the refund may take up to 2 months upon your successful self-application after the workshop ends. Participants who do not fulfill ANY of the above criteria will NOT be eligible for UTAP funding.


To apply for UTAP Funding,

Please submit an online application within 6 months after the workshop ends:


UTAP Step-by-Step Application Guide:


For more information on UTAP, please visit / email / call the NTUC Membership hotline at 6213 8008.





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For enquiries, please send an email to

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