AIGP Exam Prep Ep. 2 | Fundamentals of Machine Learning (ML)

You can't govern what you don't understand, and the systems you'll be asked to secure are built on these exact concepts.

In this video, we visually break down the fundamentals of Machine Learning, from the core vocabulary and workflow to the processes and emerging AI concepts that are reshaping what governance must urgently keep up with, all mapped out so you can see where oversight and controls need to be applied.

📌 What You'll Learn:
0:00 – Introduction
0:56 – The 5 key ML terms you need to know
2:40 – How Machine Learning works (3-stage ML Workflow)
4:02 – Important ML Processes
5:12 – Emerging AI Concepts

📌 Key Takeaways:
→ Input Data is your first and most critical control point. Biased input produces biased decisions, and that failure begins long before the model is ever deployed.
→ The ML Workflow has three stages: Learns, Builds Model, Performs Tasks. Governance stakes are highest at the final stage, where real people are affected by autonomous decisions at scale.
→ Transfer Learning saves time, but risks transfer too. Biases and data quality issues from the original model carry directly into every new application built on top of it.
→ Fine Tuning can make a model behave very differently from its original. It must be independently evaluated with its own documentation and formal sign-off before deployment.
→ Agentic AI is one of the biggest accountability challenges of our time. When a system takes multiple autonomous actions to reach a goal, tracing responsibility for harm becomes genuinely difficult.
→ RAG isn't just about the model, it's about every data source the model reaches into. Governing RAG means governing retrieval, not just generation.

💡 Who Is This For?
✅ Professionals preparing for the AIGP certification exam
✅ Designed for professionals aiming to grow their career in AI Governance, Risk & Policy
✅ Anyone who wants to understand key concepts of AI governance, compliance, and responsible AI

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Видео AIGP Exam Prep Ep. 2 | Fundamentals of Machine Learning (ML) канала Himanshu Jha | Sutra Academy