Responsible AI, Alignment, Red-Teaming & Safety
Master AI safety frameworks, RLHF, DPO, jailbreak defenses, guardrails, and regulatory compliance.
The assessment unlocks once you have worked through the lessons.
Independent provider. Not an accredited awarding body. Not a regulated qualification.
What You Will Master
- Understand RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Preference Optimization)
- Perform adversarial red-teaming and defense against prompt injection / jailbreaks
- Implement real-time input & output safety guardrails (Llama-Guard, NeMo Guardrails)
- Detect, measure, and mitigate model bias, toxic generation, and hallucinations
- Comply with global AI governance standards including the EU AI Act and NIST AI RMF
Skills Acquired
Prerequisites
- Basic understanding of LLM concepts and generative AI workflows
- Interest in ethics, system security, or legal/compliance frameworks in tech
Curriculum Syllabus
4 modules · 4 lessons · 6 min · one assessment
Module 1: AI Alignment Foundations: RLHF, DPO & Constitutional AI
How raw next-token predictors are aligned to be Helpful, Honest, and Harmless (HHH).
Module 2: Adversarial Red-Teaming & Prompt Injection Defenses
Direct and indirect prompt injections, jailbreaks, data exfiltration, and defense-in-depth.
Module 3: Hallucination Mitigation & Output Verification
Techniques for measuring grounding, factual consistency, and automated self-reflection.
Module 4: Global AI Governance & Compliance Frameworks
EU AI Act risk tiers, NIST AI RMF, bias audits, and algorithmic transparency.
Md. Rajib Hawlader
Principal AI Research Scientist, NeuroLearn AI Labs
Writes and maintains the NeuroLearn AI curriculum.
Ready to Begin Responsible AI, Alignment, Red-Teaming & Safety?
Self-paced curriculum with free instant certificate issuance upon passing the evaluation.
Start First Lesson