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Not just AIGP Certification Mastery, but your path to becoming an AI Governance Practitioner

March Cohort

March 31 - May 3

AI Governance Practitioner, Ex-Stanford 

Niharika Srivastav

AIGP, Certified AI Governance Practitioner

Chief AI Officer, CISSP,Author, Harvard 

Sanjay Saxena

Chief AI Officer, Ex-Harvard, Deloitte, KPMG

Level Up Your Career with In-Demand AI Governance Skiils/ Launch Your AI Governance Career

Feb Cohort

Turn AI Governance Into Your Competitive Advantage!Limited Time Offer: Use code 20AIGP for 20% discount As AI adoption accelerates globally, organizations face mounting risks around ethics, compliance, bias, security, and accountability. Without proper governance, AI systems can cause reputational damage, legal liability, and erosion of trust. Hence, organizations urgently need qualified AI governance professionals.This is an INCREDIBLE opportunity! Position yourself at the forefront of this high-demand field by mastering AI governance and earning your AIGP certification (by IAPP - International Association of Privacy Professionals) .✅ No prior AI knowledge required, we'll cover that! ✅ No coding skills required at all. Period.What Makes Our 4-Week Program Stand Out:✓ Visual and Engaging Learning✓ Complex Legal Frameworks and Technical Concepts Super Simplified✓ Real Projects and Real Deliverables✓ Live Lessons and Repeats of Live Lessons to Accommodate Different Time Zones✓ Office Hours✓ Unlimited Retakes of the Bootcamp✓ 1:1 Guidance for Your Challenges Ready to future-proof your career? Join us and become the AI Governance expert the world is looking for.

Become an AI Governance Professional + Ace the AIGP Certification Exam. 

Necessary AI Knowledge 

Why AI Governance?

Laws, Regulations, and Standards -  Simplified

AI Development Governance (You are not going to code)

Deployment and Monitoring

Master Organizational AI Governance 

Unlock AI innovation without compromising reputation, security or regulatory compliance.

This course is for you if want to:

Anybody who wants to ride the AI wave (No prior knowledge of AI required)

Product &amp; Project Managers/Directors, IT &amp; Business Professionals, Consultants

Legal Teams, Security and Privacy Professionals

Learn how to uncover AI vulnerabilities, run real attacks, and apply defenses that secure systems in production.

AI Governance & Cybersecurity Researcher

Krystal Jackson

AI Standards Development Researcher

Ran the 1st AI Red Teaming CTF w/ OpenAI

Sander Schulhoff

AI researcher. Founder of Learn Prompting. AI security expert.

Cohort 6

Cohort 7

The #1 AI Red Teaming Course. Taught by <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.hackaprompt.com/">HackAPrompt</a>, creators of the 1st AI Red Teaming CompetitionPrompt injection attacks are the #1 security vulnerability in AI systems. HackAPrompt's research helped OpenAI increase their model's resistance to prompt injections by up to 46%. Our recent research with OpenAI, Anthropic, and Google DeepMind found humans outperform automated AI Red Teaming.That's why companies need trained AI Red Teamers, and why we built this course.Using HackAPrompt, you'll gain hands-on experience identifying prompt injections, jailbreaks, and adversarial attacks – learning to break AI systems and secure them.Plus, access recorded hacking sessions with top AI Red Teamers who share their favorite techniques, including:<ul><li>Pliny the Prompter – World's most renowned AI jailbreaker</li><li>Johann Rehberger – Built Microsoft Azure Red Teams</li><li>Richard Lundeen – Microsoft AI Red Team Lead</li><li>Valen T. – 1st in Anthropic's Red Teaming competition</li><li>&amp; more!</li></ul>The training prepares you for our <a target="_blank" rel="noopener noreferrer nofollow" href="https://learnprompting.org/certificates/ai-red-teaming-professional-certification">AIRTP+ certification exam</a>, which has certified 100's from Microsoft, Google, Capital One, IBM, ServiceNow, and Walmart.For enterprise training: <a target="_blank" rel="noopener noreferrer nofollow" class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" href="mailto:team@learnprompting.org">team@learnprompting.org</a>

Your AI Systems Are Vulnerable... Learn how to Secure Them!

Understand How AI Systems Fail

Build Core Red Teaming Skills

Design Practical and Effective AI Defenses

Secure AI Systems Through Real-World Projects

Security, trust, and safety professionals who need practical ways to evaluate AI risks, run red team tests, and improve system reliability.

PMs and product leads who want to understand AI vulnerabilities and make informed decisions about safety, risk, and system behavior.

Engineers and technical ICs who want practical skills to test AI behavior, uncover weaknesses, and build more secure AI features.

Translate the NIST AI RMF into scalable AIMS. Shift from managing risky pilots to driving governed, enterprise-scale AI product velocity.

Principal AI Strategist, ISO 42001 AIMS

The Home Depot

WCTC

Northwestern Mutual

Omnicom Media

SC Johnson

Eric Dabols

AI Product Leader driving governed, enterprise-scale ML infrastructure.

Q2 2026 Enterprise Sprint: AIMS & NIST AI RMF

Most enterprise AI initiatives stall in the pilot phase. As product and risk leaders, we are expected to drive immediate value from raw machine learning capabilities. But without structured governance, moving from a proof-of-concept to production creates a massive bottleneck. You aren't just shipping features—you are managing regulatory exposure, cross-functional friction, and system interdependencies.This executive sprint cuts through theoretical noise. We will translate the static NIST AI RMF into a living, operational AI Management System (AIMS). I will share the exact playbooks and ISO/IEC 42001 certified protocols required to govern product velocity at scale. This is the Applied AI Framework™ (AAIF)—the operational architecture used to safely migrate 158 legacy models to Vertex AI, delivering a +29% incremental lift.You will leave this 1-day intensive with actionable templates for Strategy &amp; Alignment, Discovery &amp; Validation, and Responsible Usage Governance. We will shift your organization's posture from reactive compliance to proactive execution.

The actionable playbook to operationalize the NIST AI RMF and vendor governance.

Operationalize the NIST AI RMF

Architect Compliance Velocity with AAIF™

Execute Discovery & Validation Protocols

Enforce Responsible Usage Governance

Product Managers &amp; AI Strategists: You own the roadmap and need to bridge raw ML capabilities with governed, enterprise-scale execution.

AI Data Specialists &amp; ML Architects: You build the models but need robust AIMS infrastructure to safely deploy them into production.

AI Governance &amp; Risk Leaders: You must translate static regulatory frameworks into agile protocols that accelerate product deployment.

Master AI & LLM security through CTF-style cohort, tackling real-world attacks, defenses, adversarial threats, and Responsible AI principles

Hands-On AI Attack & Defense Cohort.

Abhinav Singh

International Trainer & Speaker, security researcher & consultant.

Cohort 5

Can prompt injections lead to complete infrastructure takeovers? Could AI applications be exploited to compromise backend services? Can data poisoning in AI copilots impact a company's stock? Can jailbreaks create false crisis alerts in security systems? This immersive, CTF-styled cohort in GenAI and LLM security dives into these pressing questions.Engage in realistic attack and defense scenarios focused on real-world threats, from prompt injection and remote code execution to backend compromise. Tackle hands-on challenges with actual AI applications to understand vulnerabilities and develop robust defenses. You’ll learn how to create a comprehensive security pipeline, mastering AI red and blue team strategies, building resilient defenses for LLMs, and handling incident response for AI-based threats. Additionally, implement a Responsible AI (RAI) program to enforce ethical AI standards across enterprise services, fortifying your organization’s AI security foundation.

Live, hands-on, CTF-style

Understand Injection Attacks and Jailbreaks on AI systems

Perform structured AI red teaming using industry frameworks

Execute and defend against adversarial & multi-agent attacks

Build and deploy LLM security tooling and enterprise-grade defenses

Operationalize AI SecOps, threat modeling, and incident response

CISOs &amp; Security practitioners looking to implement AI security best practices.

Security professionals seeking to update their skills for the AI era.

Red &amp; Blue team members.

Empower your team with real advice and hands-on skills to build privacy into today's AI workflows and systems. 

Author of Practical Data Privacy

Katharine Jarmul

Author of Practical Data Privacy, Specialist in AI/ML Systems

Cohort 1

Ensure your AI platforms and products are ethically sound and legally compliant. This intensive course equips you with the essential skills for modern AI privacy engineering, offering a blend of cutting-edge best practices and practical implementation strategies. Through live sessions, collaborative design workshops, and a capstone project simulating a real-world challenge, you'll gain expertise in defining privacy, assessing and mitigating risks, implementing pseudonymization and input sanitization, and integrating guardrails into AI workflows. This course is designed for mid-career and senior-level software engineers, data engineers, machine learning engineers, and privacy professionals seeking to enhance their expertise in a rapidly evolving field. Participants will work collaboratively in multidisciplinary teams, mastering not only technical skills but also crucial concepts in architecture, risk assessment, and mitigation prioritization. With the increasing use of sensitive data in AI products, these skills are in-demand and future-proof.

Build Privacy Engineering into AI/ML Systems

Identify actionable privacy risks in AI systems

Evaluate and implement reasonable controls

Architect privacy in AI workflows

Evaluate and test systems with a focus on privacy

You should be familiar with Python and able to use normal Python data libraries. You are willing to adapt code and build out AI workflows.

Data, Software and Machine Learning Engineers (Target Audience)

You have technical chops and either want to expand them or integrate them into your work with AI/ML systems

Privacy Professionals

You are comfortable in technical conversations and want to increase your knowledge of AI privacy risk.

Security

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