Anthropic training programmes

Over the last week I have completed three Anthropic training programmes to expand my use of AI tools from Copilot and Gemini. While the courses focus on Claude, the value goes far beyond learning a particular AI tool. I completed:

• Claude 101
• AI Fluency Framework & Foundations
• Claude Code in Action

Claude 101 provides a solid grounding in how to work effectively with large language models. It covers prompt design, structuring requests, and understanding where AI can genuinely add value versus where human judgement remains essential.

AI Fluency Framework & Foundations takes a broader view. Rather than concentrating on technology alone, it explores how individuals and organisations can develop the skills, mindset and practices needed to adopt AI successfully. It reinforces an important lesson about becoming AI-enabled is as much about people and ways of working as it is about the tools themselves.

Claude Code in Action was particularly interesting from a practical perspective. It demonstrates how AI can support software development workflows, automate repetitive tasks, assist with code generation and review, and help teams move faster while maintaining quality. Even for those of us who are not full-time developers, it offers valuable insight into how AI is changing the way technical teams work.

The skills I learned on a this tool cover the tool usage but are more about people, skills, governance, and trusted data.

AI Security & Governance Certification

Always interested to check out different learning routes. This was a good introductory course and certification for AI Security & Governance to demonstrate awareness of AI challenges.

Having spent many years working in Data Governance and, more recently, AI Governance, I found the Securiti AI Security & Governance Certification to be a particularly worthwhile programme. The course does an excellent job of connecting governance principles with the practical realities of AI adoption. Topics such as AI model discovery, risk assessment, data and AI mapping, governance frameworks, and regulatory compliance are presented in a way that feels relevant to the challenges organisations are dealing with today. My biggest takeaway was that successful AI governance requires far more than policies and controls. It depends on understanding how data, models, processes, people, and regulations intersect across the organisation. The certification provides a strong foundation for anyone looking to develop a broader and more operational view of AI governance.

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GRAICE Foundation Training Principles of Responsible AI Governance

I am pleased to share I have completed the GRAICE Foundation Training Principles of Responsible AI Governance and am certified for foundational competency in GRACIE, Humanity's Operating System for AI. 

GRAICE is a robust governance operating system geared toward instilling confidence and accountability in AI systems on a global scale. It has 6 foundational values, 7 operational pillars and a 3 teir assurance model.