Certification
Certification in Building Self-Improving AI Agents
Become certified in evaluating self-improving AI systems across diversity, verification, data, and energy constraints. You'll pinpoint where approaches fail, propose practical next steps, and translate trade-offs into engineering decisions.
The exam
Take the certification exam
Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.
What the exam covers
2 questions from each of the 9 chapters of the course
18 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01Course recap2:41
- 02Orchestration and verifiers2:19
- 03Test-time scaling and diversity2:00
- 04Meta-verification5:20
- 05Multi-agent fine-tuning8:00
- 06Iterative proof improvement2:13
- 07Self-proposed tasks and curricula18:27
- 08Future inference and efficiency14:00
- 09Open questions12:42
This certification, Self-Improving AI Agents: Open Problems & Future Directions, is a video course that gets to the heart of why self-improving AI keeps hitting walls. You'll come away with a real competitive advantage, sharper decision-making, and a future-proof skill set that most people in the field simply don't have yet. If you're ready to see what's next before it happens, this course is your ticket.
This certification covers the following topics:
- A Different Kind of Intelligence
- Rethinking the Self-Improvement Loop
- The Diversity Bottleneck: Why One Brain Isn't Enough
- The Meta-Verification Problem: Who Watches the Watchmen?
- Breaking the Human Data Barrier: The Proposer-Solver Framework
- The Efficiency Frontier: Making Every Watt Count
- The Open Questions: Where Do We Go From Here?
- Putting It All Together: A Roadmap for the Future
- The Road Ahead