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Responsible AI, LLM Evaluation & Governance

Test AI quality, safety, bias, privacy, security, and compliance using practical evaluation frameworks, red teaming, monitoring, and governance.

10 weeks Intermediate
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Responsible AI, LLM Evaluation & Governance training course at Success Root Technologies
AI-enabled curriculum

AI tools included in this course

Learn the core subject and use current AI assistants responsibly for faster analysis, creation, debugging, automation, and decision-making.

01OpenAI Evals02promptfoo03LangSmith04OWASP GenAI guidance05NIST AI RMF
What you will learn

A current, project-led curriculum

Move from clear foundations to complete implementation through guided labs, reviews, and a portfolio-ready capstone.

  1. 01Responsible AI principles and risk classification
  2. 02Evaluation datasets, metrics, and test design
  3. 03Bias, hallucination, privacy, and robustness testing
  4. 04Prompt injection, red teaming, and security controls
  5. 05Monitoring, incident response, and governance
  6. 06AI assurance assessment capstone
Career outcomes

Skills you can demonstrate

Design repeatable AI evaluation programs

Test LLM applications for quality and safety

Document risks, controls, and governance decisions

Create an AI assurance portfolio assessment

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