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Professional

Professionals

Technical depth on LLMs, agents, RAG and governance — for those building or leading with AI.

1

Foundations of LLMs

Transformers, tokenisation, context windows, and how LLMs generate text.

4 lessons

Start
1Transformer Architecture2Key Model Parameters3Navigating the Model Landscape4Hallucinations and Reliability
2

Prompt Engineering

Techniques from zero-shot to chain-of-thought, with evaluation frameworks.

4 lessons

Start
1Core Prompting Techniques2System Prompt Engineering3Evaluating LLM Systems4Fine-Tuning vs. Prompting
3

AI in Business

Strategy, ROI, change management, and building the case for AI adoption.

4 lessons

Start
1Identifying AI Use Cases2Implementing AI in Organisations3Legal Considerations for AI in NZ4AI Vendor Evaluation and Procurement
4

Building with AI

APIs, orchestration, tool use, and multi-agent patterns in production.

4 lessons

Start
1LLM Application Architecture2AI Agents and Tool Use3Monitoring AI in Production4AI Application Security
5

Retrieval-Augmented Generation

Architecture, chunking, embeddings, vector stores, and evaluation.

3 lessons

Start
1Retrieval-Augmented Generation (RAG)2Vector Databases and Embeddings3Advanced RAG Techniques
6

AI Governance and Risk

Policy, model risk, auditing, bias mitigation, and regulatory frameworks.

4 lessons

Start
1Responsible AI Frameworks2The EU AI Act3AI Regulation in NZ and Australia4Global AI Governance Landscape
7

AI Strategy

Roadmaps, capability building, vendor evaluation, and organisational transformation.

3 lessons

Start
1Building an AI Strategy2AI Talent and Workforce Strategy3AI Competitive Dynamics