Introduction to Reinforcement Learning from Human Feedback (RLHF)

You’ve been hired as an AI Engineer at Globomantics to fix a misaligned LLM. This course will teach you how to use RLHF to design feedback systems and develop value-based alignment strategies for responsible AI deployment.
What you'll learn

Globomantics’ flagship AI assistant is under scrutiny—its responses are inconsistent, misaligned with brand values, and potentially harmful in sensitive contexts. Leadership has tasked you, a newly hired AI Engineer, with leading the charge to realign the model and restore user trust. In this course, Introduction to Reinforcement Learning from Human Feedback (RLHF), you’ll learn to apply RLHF to identify misalignment issues, design ethical feedback systems, and build strategies that align AI behavior with human values. First, you’ll explore what RLHF is, why it exists, and how it helps large language models (LLMs) better reflect human intent. Next, you’ll learn practical techniques for incorporating human feedback, including how to collect, structure, and apply it responsibly. Finally, you’ll develop strategies to align AI outputs with ethical values, balancing real-world expectations, diverse users, and organizational risk. The course is delivered in video clips, paired with a learner guide and a scenario-based capstone project. When you’re finished, you’ll have the skills and insight needed to design and communicate an RLHF-based alignment plan—equipping you to take the lead on responsible AI implementation in real-world engineering teams. As part of this course, you’ll also complete a practical action plan outlining your RLHF recommendations and deployment strategy for the Globomantics team.

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