Fine-Tuning LLM Model to Supercharge Your Model

Topic 1 Introduction to Large Language Models (LLM) and AI Agents

• Overview of transformer architecture and attention mechanisms in LLMs
• Introduction to AI agents
• NLP applications Powered by LLM and AI agents
• Use cases of LLMs and AI agents

Topic 2 Retrieval-Augmented Generation (RAG)

• Introduction to Retrieval-Augmented Generation (RAG)
• Use cases of RAG
• Overview of tokenization and word embeddings
• Overview of chunking strategies and vector databases
• Build a RAG system

Topic 3: Fundamentals of Fine Tunning LLM

• Fundamentals of LLM Fine Tuning
• Supervised Fine-Tuning (SFT) for custom LLM Tasks
• Parameter Efficient Fine Tuning (PEFT)
• Low-Rank Adaptation (LoRA) for fine tuning LLM
• Group Relative Policy Optimization (GRPO)
• Reinforcement Learning (RT Learning) for fine tunning

Topic 4 Fine Tuning LLM Implementation and Deployments

• Overview of Hugging Face Fine Tuning Libraries
• Implementing Fine Tuning wiht Hugging Face Libraires
• Using Hugging Face datasets and tokenizers for LLMs fine tunning
• Deploying and testing Fine-Tuned models

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

• AI Engineer
• Machine Learning Engineer
• NLP Engineer
• LLM Fine-Tuning Specialist
• AI Research Scientist
• Data Scientist
• Deep Learning Engineer
• AI Solutions Architect
• MLOps Engineer
• AI Product Manager
• Conversational AI Developer
• AI Infrastructure Engineer
• Natural Language Processing Researcher
• AI Consultant
• Machine Learning Operations Specialist
• AI Application Developer
• Data Engineer
• AI Technical Lead
• Prompt Engineer
• AI Systems Integration Specialist

Solomon Soh Zhe Hong: Solomon is ACTA certified and has trained and coached over 100 professionals in the area of data science, python programming and coding. Solomon is a Certified AI Engineer Associate by AI Singapore and holds certifications in Alibaba Cloud Architect and Alteryx respectively. Solomon interests include Reinforcement Learning, Natural Language Processing and Time-Series analysis.

Alfred Yap Swee Leong: Alfred Yap is an ACLP certified trainer with strong financial and shopper marketing domain background and extensive experience in information technology. In addition, he is both an IBM certified Cloud Computing Practitioner and an IBM Enterprise Design Thinking Practitioner.
Alfred Yap has spent decades teaching adult learners since the 90s. Kickstarting his teaching career as a trainer for Oracle University. Thereafter, he has had vast experience conducting ICT related training to various companies in the Consulting, Media, and Training industry.
Alfred Yap earned his undergraduate degree from USF, America and master degree from NTU, Singapore majoring in Knowledge Management. His current interests include Cyber Security, Cloud computing and Blockchain.