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Beginning Artificial Intelligence Through Neuroscience (Synchronous e-learning)
Programme Code: TGS-2020513214
Mode of Delivery
Online (Live)
Duration
2 Half-Days
Date / Time
- 27/07/2024 9:00 am - 12:30 pm, 03/08/2024 9:00 am - 12:30 pm (Run 1 - Register by 12 July)
- 07/09/2024 9:00 am - 12:30 pm, 14/09/2024 9:00 am - 12:30 pm (Run 2 - Register by 23 Aug)
Refer to the dates above for respective deadlines.
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
Course Agenda
.
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
Run 1: Reg closes on 12 July
Run 2: Reg closes on 23 Aug
Terms & Conditions / Cancellation Policy
- The scheduled course run will proceed only if the minimum class size is met.
- We reserve the right to cancel or postpone any course or change the venue due to unforeseen circumstances.
- In the event of a cancellation and the fee has been paid, a full refund will be made to registrants.
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