Advanced Certificate in Applied Artificial Intelligence (AI) Programming Module 9: Retrieval Augmented Generation (RAG) Programming
- Analytics & Tech
- Artificial Intelligence
- Innovation & Business Improvement
2 Full Days (Weekdays)
Who Should Attend
- Natural Language Processing Engineers
- Data Scientists and Machine Learning Practitioners
- Software Developer
- Product Managers and Business Analysts
- AI Enthusiasts
- Professionals in Content Creation and Publishing
PREREQUISITES
- Basic programming experience using Python
- Knowledge of NumPy and Pandas (covered in Module 2)
- Recommended to have knowledge of Machine Learning (covered in Module 3)
- Recommended to have knowledge of Deep Learning (covered in Module 4)
- Recommended to have knowledge of AI applications development (covered in Module 5)
Overview
Retrieval Augmented Generation (RAG) is one of the most popular use cases of Large Language Models (LLMs). It allows you to integrate LLMs with your organisation’s proprietary data. In this 2-day module, participants will dive deep into the principles, techniques, and applications of RAG, gaining hands-on experience in harnessing its capabilities to create intelligent and contextually rich text generation systems. Whether you are a seasoned practitioner or a newcomer to the field, this module offers an invaluable opportunity to master the cutting-edge technology driving the future of natural language understanding and generation.
Learning Objectives
At the end of the 2-day module, participants will be able to:
- Gain a deep understanding of the principles, architecture, and techniques underlying Retrieval Augmented Generation (RAG), including the integration of retrieval-based and generative models
- Familiarise themselves with leading RAG frameworks and libraries, learning how to effectively utilize them for text generation tasks and integrate them into existing systems
- Gain hands-on experience in implementing RAG models, including fine-tuning pre-trained models and customizing them for specific applications and use cases
- Learn how to leverage retrieval mechanisms to enhance the contextuality and relevance of generated text, ensuring more accurate and coherent outputs
- Explore techniques for optimizing the performance and efficiency of RAG models, including batch processing, caching, and parallelization strategies
- Develop proficiency in evaluating the performance and quality of RAG models using appropriate metrics and evaluation techniques, ensuring robust and reliable text generation systems
- Apply RAG techniques and frameworks to real-world text generation tasks and scenarios, such as question answering, summarization, and conversational AI, demonstrating the practical utility and effectiveness of RAG technology
- Stay informed about the latest advancements and research trends in RAG technology, enabling continued learning and adaptation to evolving best practices and methodologies.
Assessment
As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.
Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$654 (After SSG Funding 70%) |
$254 (After SSG Funding 70% |
$654 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
|
International Participant |
$2,180 (No Funding) |
$2,180 (No Funding) |
$2,180 (No Funding) |
All prices include 9% GST
Please note that the programme fees are subject to change without prior notice.
Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.
Self Sponsored
SkillsFuture Credit
Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.
This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.
Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).Workfare Skills Support Scheme
From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.
Company Sponsored
Enhanced Training Support for SMEs (ETSS)
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents
- Trainees must not be a full-time national serviceman
- Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
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