Infocomm

Work-Study Post-Diploma (Specialist Diploma in Applied Generative Artificial Intelligence)

Open for Registration

Course Type

SkillsFuture Work-Study Programmes

Specialist Diplomas

Infocomm

Artificial Intelligence

The Specialist Diploma in Applied Generative Artificial Intelligence (SDGAI) course is designed to provide a comprehensive introduction to the principles, techniques, and applications of Artificial Intelligence (AI) and Generative AI.

This course is open for registration. Apply here.

Hands typing on a laptop with digital interface overlays showing AI icons and code.

About course

Course objectives

Upon completion of the Work-Study Post Diploma (Specialist Diploma in Applied Generative Artificial Intelligence) programme, graduates will be able to:

Explain the business cases of applied and generative artificial intelligence for different use cases or contexts.
List and describe the various technologies, frameworks, and platforms for applied and generative artificial intelligence.
Differentiate major Machine Learning, Deep Learning and Generative AI models.
Architect or design solutions that apply one or more artificial intelligence concepts and technology using Machine Learning, Deep Learning or Generative AI models.
Build, test, and deploy a complete IT solution that applies artificial intelligence in industry use cases.

Course description

This course will guide participants through the fundamentals of AI, including machine learning, deep learning, and neural networks, before delving into the innovative realm of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), Stable Diffusion, and Large Language Models (LLMs). Participants will also gain a deep understanding of the ethical challenges in AI development and learn to develop AI systems with ethical considerations in mind.

By the end of this course, participants will have the knowledge and skills to implement AI solutions and create generative AI models that can produce original content.

Target audiences

What is so unique about this programme?

The course is designed to prepare students for industry certifications, specifically equipping them with the necessary skills needed to take the AWS Certified Machine Learning - Speciality exam and the NVIDIA Deep Learning Institute certification.

Course structure

TPG course reference No.

TGS-2024046692

Specialist Diploma in Applied Generative Artificial Intelligence

Post-Diploma Certificate in Applied Artificial Intelligence

Module name	Module synopsis
Programming for Artificial Intelligence	This module equips students with the fundamentals of programming using Python. Students will learn how to solve problems through coding a software program. Fundamentals of software structure, variables, selection, and iteration constructs will be covered. Students will be able to create software to solve simple programming problems related to AI.
Machine Learning Fundamentals	This module covers basic concepts in machine learning and the use of various open-source libraries like scikit-learn, Tensorflow and Keras to build basic machine learning applications with perceptron, K nearest neighbours, neural networks, SVMs, decision trees and unsupervised learning. Students will also be introduced to XGBoost and other ensemble methods to solve classification and regression problems.
Deep Learning Fundamentals	This module aims to introduce participants to the key topics associated with deep learning. This module will cover the fundamental underpinnings of Artificial Neural Networks (ANN), Convolution Neural Networks (CNN), Recurrent Neural Networks (RNN) and Long-Short Term Memory (LSTM) networks, and the fundamentals will be supported with practical work that involves participants developing and deploying an ANN, CNN, RNN, and LSTM.

Post-Diploma Certificate in Generative Artificial Intelligence

Module name	Module synopsis
Developing Ethical AI Systems: Data, Values, and Process	This module offers an introduction to open-source data platforms and frameworks for storing large data volumes. It provides an overview of the machine learning pipeline, including data management, high-throughput model training/evaluation, and real-time data processing. Participants will examine ethical/legal issues in AI using basic reasoning frameworks and principles, with a focus on privacy and data protection. Additionally, this module will cover AI project management methodologies like agile development, resource planning, and risk management tailored for AI projects. Concepts of explainable AI and model governance are introduced to ensure transparency, fairness, and compliance of AI systems.
Vision Models for Generative AI Applications	This module will journey through the world of vision models, making them work for tasks like understanding pictures and creating new, unique images. Starting with the basics, showing how these models learn from images. Then, the module will dive into how to tweak these models to make them even better, using tools from AWS, NVIDIA, and the open-source community. Through hands-on experience, students will learn how to fine-tune these models for tasks like recognising what is in a picture and even teaching the model to create its own images. The module is designed to be interactive and practical, giving students the skills needed to use these vision models effectively in the exciting world of generative AI.
Large Language Models for Generative AI Applications	This module delves into the technicalities of Large Language Models (LLMs), emphasising their application in text-driven AI tasks. Starting with an insight into model training, the course intensifies its focus on fine-tuning these models for specific tasks such as text generation or summarisation, leveraging technologies from AWS and NVIDIA, alongside a variety of open-source resources. Students will gain a practical understanding of adjusting and deploying LLMs by diving into hands-on sessions that involve fine-tuning parameters and mastering deployment techniques. This approach ensures a comprehensive grasp of how to utilise these powerful models, employing a blend of industry-standard technologies and open-source tools to implement LLMs in diverse AI applications effectively.

Entry requirements

WSP Eligibility

Singaporeans and Singapore Permanent Residents who are:

Applicants should possess a relevant local polytechnic Diploma in Information Technology or Computer Science within three years of graduation from the Polytechnics or the Operational Ready Date (ORD) for full-time National Servicemen, or
within five years of graduation from the Polytechnics, and if their employer is a participating company.

Course Entry Requirement

Applicants should preferably be a graduate of a Polytechnic with a diploma related to the following clusters.

Applied Sciences
Business & Management
Engineering
Health Sciences
Information & Digital Technologies
Media & Design

Admission will be reviewed and approved by the polytechnic on a case-by-case basis.

Conditional Offer

Graduating students (in their final academic year) from a local polytechnic may apply for the programme.

Click here for more information on how to apply for the programme and receive a Conditional Offer.

Interested applicants may submit their interest via https://for.edu.sg/rp-wsp to be contacted for a job matching opportunity before applying for the course.

Course schedule

Course schedule information

Commencement Date	Duration	Mode and Venue	Schedule	Application Start and End Date

Note: RP reserves the right to reschedule/cancel any programme and amend information without prior notice.

Refer to the Academic Calendar on the Republic Polytechnic website or key dates and important information to help you plan your learning journey.

How to apply?

Click the Apply button to submit your application. You will receive a confirmation once it has been successfully submitted.
If you are unable to attend the current course dates, click Register Interest button to be notified of future intakes.
If the Apply button is not visible, it means applications are currently closed. You can still click Register Interest button to leave your details, and we’ll notify you when the next application window opens.

Company Sponsorship

If your company is sponsoring your course:

Ask your company’s course coordinator to log in to the STEP portal with Corp Pass and create a corporate application link for you.
Use this link to submit your application.
Need help? Check out our step-by-step guide for instructions on using the STEP portal.

Need more information?

Visit the Course Application page for full details on the application process.

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