WSQ Fine Tuning Generative AI Models for Real World Applications
About This Course
Course Overview
The WSQ Fine Tuning Generative AI Models for Real World Applications course equips learners with the practical and theoretical expertise to develop and fine-tune generative AI models using state-of-the-art deep learning architectures. Participants will explore foundational concepts in probability, statistics, and deep learning algorithms such as GANs, VAEs, and Transformers, implementing models with libraries like TensorFlow, PyTorch, and Keras.
The course emphasizes robust data preparation, including dataset cleaning, de-duplication, embeddings, and tokenisation. Learners will apply neural optimisation techniques, train models on benchmark datasets, evaluate performance with appropriate metrics, and apply targeted fine-tuning strategies such as supervised and parameter-efficient fine-tuning. The course is designed for learners with foundational knowledge of machine learning and programming.
Course Outline
- Generative AI Theory
- Generative AI Data Preparation
- Generative AI Model Training
- Generative AI Model Fine Tuning
Duration & Schedule
Fee & Funding
Nett fees shown after SSG subsidy, subject to eligibility and funding caps. SkillsFuture Credit (SFC), UTAP and PSEA may be used to offset the nett fee.
SkillsFuture Credits, UTAP and PSEA Claimable
SkillsFuture Credits: All Singaporeans aged 25 years old and above can use their SkillsFuture Credits to fully offset the remaining fees.
UTAP Funding: In addition, NTUC members can utilise UTAP to offset up to 50% of remaining fees (capped at $500 per year).
PSEA: All Singaporeans aged 21 – 31 may use their Post-Secondary Education Account (PSEA) to offset remaining fees.
Frequently Asked Questions
Am I eligible for SSG funding support?
To qualify for SSG funding, you must be at least 21 years old, a Singapore Citizen or PR, achieve at least 75% attendance and pass the final assessment. Visit the SkillsFuture Singapore website for the full eligibility criteria.
What is the refund and withdrawal policy?
Kindly note the refund policy indicated below. Not eligible for any refund of course fees already paid if withdraw from the course without prior notice or given notice of withdrawal on or after the course commencement date.
| Refund | If trainee’s written notice of withdrawal is received |
|---|---|
| 100% | At least 7 working days before the Course Commencement Date |
| 75% | Between 4–6 working days before the Course Commencement Date |
| 50% | Between 1–3 working days before the Course Commencement Date |
| 0% | No-show or withdrawal on or after the Course Commencement Date |
What are the requirements to successfully complete the course?
To successfully complete the course and be eligible for certification, learners are required to:
- Fulfil the minimum attendance requirement stated for the course
- Complete all required assessments and course activities
- Achieve a “Competent” assessment outcome
What if I do not meet the course requirements?
Learners who do not fulfil the required attendance and/or assessment requirements may:
- Not be eligible for certification
- Not qualify for the applicable course fee funding/subsidy
- Be required to pay the difference between the subsidised fee and the full course fee, where applicable
Important: Learners are encouraged to attend all scheduled sessions and complete all assessments to ensure that the course completion and funding requirements are met.
