In Person · Sydney

29 July 2026 – 31 July 2026 · AEST

# 2026 AI Industry Training & Hackathon

A hands-on program covering practical AI implementation for enterprise teams — from strategy to production-grade deployment.

Generative AI
Neural Symbolic AI 
AI Strategy
RAG & Knowledge Systems
AI Governance

[Register Interest](/content/events/2026-ai-industry-training-hackathon#register/index.html)

This program is 3 day industry training and hackathon designed for software engineers and technical professionals who wants to build, deploy, and compete with real AI systems. It is suited to:

- Software engineers and developers building or integrating AI into their products
- Technical professionals working with large language models, agents, and AI infrastructure
- Engineers looking to gain hands-on experience with model evaluation, fine-tuning, and agentic frameworks
- Developers interested in the latest tooling from NVIDIA, LangChain, and the open-source AI ecosystem
- Participants should have a working knowledge of Python and be comfortable in a Linux/command-line environment. Capacity is limited to 40 attendees

Trainers from NVIDIA, Anthropic and LangChain

## Day 1: Building with AI

* * *

### Session 1: Where the Future Economy is Headed with Software 2.0

**Duration:** 2 hours \| **Format:** Presentation & Discussion

- Creating value in the future economy — electricity + compute + developers = revenue
- Evolution of software architectures — from monoliths to AI Agents
- The death of SaaS and the age of personal software
- The path to reasoning — RAG techniques and limitations of LLMs
- Agentic applications — what they are and why they matter
- The economics of inference — cost per token, latency vs. throughput tradeoffs, why this shapes product decisions
- Edge AI and the on-prem trend
- Gigabyte AI developer hardware introduction

* * *

### Session 2: Hands-On Lab — Building with AI, transitioning to no-manual coding

**Duration:** 6 hours \| **Format:** Lab-based

Dependencies: User to work on own laptop, requires WSL, Ubuntu

Attendees receive a Claude 1 month voucher.

**Greenfield Software Development** _(4 hours)_

- Prompt Engineering Fundamentals
- Building skills, skill composability
- Context Engineering and memory (Vector RAG, Graph RAG) - Obsidian & Graphify
- Connecting to agents using MCP servers
- Planning and designing
- Testing & iteration

**Legacy Code & Migration** _(2 hours)_

- Re-engineering and migrating legacy codebases (clean-room re-implementation)

**Patterns & Methods & Workflow**

- Architectures and patterns for AI-assisted development
- Reducing token usage (tied to context engineering and memory)
- Ways of working: the AI-augmented developer workflow
- Human in the loop, code reviews, and QA
- Debugging AI apps in production using LangSmith

* * *

## Day 2: Building AI — AI Engineering Foundations

**Duration:** 8 hours

* * *

### Session 3: Infrastructure & Models

**Duration:** 3 hours

- GB10 (Gigabyte AI Top Atom) clustering
- Environment set up, dependencies
- Hosting foundational models and short-term memory

### Session 4: Evaluation & Light Customization of LLMs

**Duration:** 2 hours

_Based on NVIDIA's Deep Learning Institute courseware_ [ref](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-34+V1)

- LLM Evaluation Fundamentals
- Running benchmark evaluation using GSM8K [ref](https://llm-stats.com/benchmarks/gsm8k)
- Parameter-Efficient Fine-Tuning (PEFT) with Low-Rank Adaptation (LoRA)
- NVIDIA NeMo Framework, NeMo Evaluator, and NeMo Customizer
- NVIDIA Inference Microservices (NIMs)
- MLflow for Experiment Tracking

### Session 5: Agents

**Duration:** 3 hours

#### LangChain Foundations (Python)

- Building simple agents
- Model Context Protocol (MCP) — what it is, building an MCP server, connecting to third-party MCP servers
- Multi-agent protocols
- Setting up a coding agent

#### Multi-modal Agents

- VLMs and VLQA

#### Openclaw

- Openclaw/Nemoclaw setup
- Setting your own coding agent (Clawcode)
- Claw automation tutorial (e.g. email automation agent)

## Day 3: Hackathon

**Duration:** 8 hours

### Logistics

- Equipment: 15 x AI Top Atoms, monitors, mouse and keyboard supplied by Gigabyte
- Number of teams: 9 teams of 4-5

### Format  
- Part 1 (30%): Teams will complete a series of AI model/LLM evaluations, in the categories of data science, LLM and Computer Vision.  
- Part 2 (30%): Teams will build Claw bots / agents to complete tasks.
- Part 3 (40%): Agent vs Agent. Teams build an agent to compete against other agents in a round-robin format.

### Award Presenters

- Department of Industry Science and Resources Representative (TBC)
- Gigabyte Australia Country Manager
- UNSW CSE Head of School

### Adjudicators

- Prof. Fethi Rabhi, Director of Studies Software Engineering, UNSW
- Prof. Amin Beheshti, Director of the Centre for Applied Artificial Intelligence, Macquarie University
- Adj Assoc Prof. Alan Hsiao, UNSW and CEO Cognitivo
- Haritha Thilakarathne, Senior Development Relations Manager, NVIDIA