Beginning Artificial Intelligence Through Neuroscience (Synchronous e-learning)

Programme Code: TGS-2023040116

SFC-Eligible

Mode of Delivery

Online (Live)

Duration

2 Half-Days

Date / Time

  • 07/09/2024 9:00 am - 12:30 pm, 14/09/2024 9:00 am - 12:30 pm (Register by 23 Aug)

Register by 23 Aug to secure your spot in the course.

Programme Highlights

Neuroscience helped inspire deep learning, which is the basis of AI technologies such as speech recognition by personal digital assistants and face recognition for access control, and is being developed for applications such as assisted interpretation of medical images and scene analysis by self-driving cars.

Organised by the Department of Physiology, NUS Yong Loo Lin School of Medicine, this course introduces the relevant neuroscience, including the function and connectivity of the cerebral cortex, which is used to motivate the architecture of deep learning artificial neural networks. Participants will learn the mathematical and statistical concepts needed to fit models to data; beginning with simple examples such as linear regression and binary classification, followed by the application of these principles to train deep learning models. We will briefly indicate their extension to generative AI including large language models like ChatGPT.

There will be opportunities for participants to experience hands-on coding with some common AI tools. The outlook for and potential pitfalls of AI will also be examined and discussed.

Benefits of Attending

  • Appreciate fundamental AI concepts for managing AI technology
  • Acquire basic coding skills for constructing simple AI systems
  • Build and deploy a simple deep learning model

Who Should Attend

  • Allied health professionals
  • Nurses
  • Doctors
  • Teachers
  • Managers
  • Data analysts
  • IT professionals
  • Technology officers,
  • Technical advisors
  • Anyone who is interested in gaining a basic understanding of AI

Trainer Profile

Dr Andrew Tan Yong-Yi

View More

Course Agenda

 

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Topics

Day 1

AM

  • Introduction to AI
  • Practical – Linear regression
  • Neurons and simple neural networks
  • Practical – Perceptron classification

Day 2

AM

  • Object recognition
  • Practical – Digit classification website
  • AI Anecdotes

Pre-Requisites and Assessment

A background knowledge in calculus at the level of H1 or AO-level mathematics, or equivalent will be helpful. However, those who have not studied calculus are also welcome to register, as we will give a beginner’s introduction to calculus during the course.

Assessment will be project-based. Learners must pass all assessment components to successfully complete the course and receive a Certificate of Completion. Learners may have to bear the full course fee if they fail to meet this requirement.

Awards and Certification

All participants will receive a Certificate of Completion.

Hear from Past Participants

Course Fee

International Participants

Singapore Citizens1 39 years old or younger

Singapore Citizens1 40 years old or older eligible for MCES2

Singapore PR

Enhanced Training Support For SMEs3

Full Course Fee

$850

$850

$850

$850

$850

Less: SSG Grant Amount4

$595

$595

$595

$595

Nett Course Fee

$850

$255

$255

$255

$255

9% GST on Nett Course Fee

$76.50

$22.95

$22.95

$22.95

$22.95

Total Nett Course Fee Payable including GST

$926.50

$277.95

$277.95

$277.95

$277.95

Less Additional Funding if Eligible Under Various Schemes

$170

$170

Total Nett Cost Fee Payable, Including GST, after additonal funding from the various funding schemes

$926.50

$277.95

$107.95

$277.95

$107.95

1) All self-sponsored Singaporean aged 25 and above can use their SkillsFuture Credit to pay for the course fee.

2) Mid-Career Enhanced Subsidy (MCES): Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fee.

3) Enhanced Training Support for SMEs (ETSS): SME-sponsored employees (Singapore Citizens and PRs) may enjoy subsidies up to 90% of the course fee.

4) Learners must pass all assessment components to successfully complete the course and receive a Certificate of Completion. Learners may have to bear the full course fee if they fail to meet this requirement.

Application Deadline

Reg closes on 23 Aug

Terms & Conditions / Cancellation Policy

  1. The scheduled course run will proceed only if the minimum class size is met.
  2. We reserve the right to cancel or postpone any course or change the venue due to unforeseen circumstances.
  3. In the event of a cancellation and the fee has been paid, a full refund will be made to registrants.

 

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