Overview
Gain essential theoretical knowledge and hands-on skills to develop, optimise, and deploy Large Language Models (LLMs) in enterprise settings. Gain a competitive edge in today's AI-driven job market by mastering one of its most coveted skills. Reduce dependence on external vendors like AWS and GCP and ensure your LLM deployments are optimised, scalable, and ethical. Fine-tune real-world use cases using leading models such as GPT-4 Turbo from OpenAI and Claude from Anthropic or explore open-source options like Llama 2 from Meta and Hugging Face.
Key Takeaways
At the end of this programme, you will be able to:
- Understand foundational concepts of Large Language Models (LLMs), transformer architecture, and their evolution
- Learn and apply strategies to fine-tune pre-trained LLMs with available foundational models for specific enterprise tasks
- Enhance LLMs using reward-based reinforcement learning for performance optimisation
- Overcome deployment challenges in production environments and optimise LLMs for efficient training and inference with model and data parallelism
- Apply theoretical knowledge through practical labs, building and deploying LLMs in real-world scenarios
Who Should Attend
- Please refer to the job roles section.
- Information technology professionals who are planning to build their enterprise LLMs or fine-tune LLMs with foundational models.
- CTOs and technical leaders, data engineers, data scientists, ML engineers, and software developers advancing in Large Language Models (LLMs) for fine-tuning, deployment, and training.
Prerequisites
This is an intensive intermediate course.
- Participants should have intermediate mathematics and statistics knowledge, e.g. calculating boolean algebra (logic), and probability.
- Participants should have intermediate computer literacy and software engineering fundamentals, e.g. using Windows or Linux or MacOS, Microsoft Office or LibreOffice, VMware or VirtualBox, and aware of web application, and client-server software architecture.
- Participants should have current or prior hands-on coding experience in one or more high-level computer programming languages, preferable in Java. Experiences with Python, R, or structured query language (SQL) would have added advantages.
- Participants without programming experience should self-study basic Java or Python.
- Knowledge of deploying applications on the cloud such as AWS and GCP are a plus.
What To Bring
No printed copies of programme materials are issued. You must bring your internet-enabled computing device (laptop, tablet etc) with power charger to access and download programme materials. If you are bringing a laptop, please see below for the tech specs:
| | Minimum | Recommended |
| Computer and Processor | 1.6 GHz or faster, 2-core Intel Core i3 or equivalent, e.g. Apple (Intel) year 2012 model and newer | Intel Core i7 or equivalent, e.g. Apple (Intel/M1/M2 chip) new models |
| Memory | 4 GB RAM | 16 GB RAM |
| Hard Disk | 256 GB disk size | 1 TB disk size |
| Display | 800 x 600 screen resolution | 1280 x 768 screen resolution |
| Graphics | Graphics hardware acceleration requires DirectX 9 or later, with WDDM 2.0 or higher for Windows 10 (or WDDM 1.3 or higher for Windows 10 Fall Creators Update). | DirectX 10 graphics card for graphics hardware acceleration |
| Others | An internet connection - broadband wired or wireless
Speakers and a microphone - built-in or USB plug-in or wireless
Bluetooth
A webcam or HD webcam - built-in or USB plug-in | |
