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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.

Privacy and Risk Leadership

Data, Software and Machine Learning Engineers

Technical Privacy Professionals (Privacy Engineers)

Privacy Leadership (technical-oriented)

How to think through AI problems end-to-end: scoping, debugging, and knowing when to pivot.

ML Engineer with 10+ years of experience

Hugging Face

DataRobot

Contextual AI

Snowflake

Snorkel AI

Rajiv Shah

Enterprise AI veteran: Shipping AI to production, with clarity and humor

Pilot Cohort

Summer 2026

AI Problem Framing is to AI teams what System Design is to software engineers and Product Sense is to PMs. Whether you're building, evaluating, or leading AI work, this is the foundational thinking skill that separates results from rework.--🚨 Summer cohort: June 2 – June 26 🚨Winter Cohort is finishedUse Code: Earlybird for 20% discount if you sign up by April 30th---What you get:🔄 The Loop, a 5-step framework you'll use to think through every AI project🧑‍🏫 Live sessions and office hours where you can bring your real problems📊 Access to 200+ case studies, the largest collection of AI reframing examples📋 Production-ready checklists for RAG, Forecasting, GenAI🎥 Lifetime access to all recordings---This course is for you if:• Your AI works in demos but fails in production• You've spent months on a model only to realize you solved the wrong problem• You lead AI work but came from engineering, product, or PMYou'll learn from 200+ AI failures in 4 weeks. You gain years of experience and recognize the scars.If you are a student or between jobs, send me a note about your current situation and why this course is important to you, and I may discount the course appropriately.

Most AI fails from bad framing, not bad models. Learn to fix that.

Frame AI problems right the first time

Diagnose what's actually broken

Own the problem, not just the solution

Steer your team past expensive mistakes

We focus on framing and strategy, not explaining what models or training means. Basic vocabulary lets us go deeper faster.

You understand what AI/ML is at a conceptual level

Real experience gives you context. The frameworks click when you can map them to projects you've actually built or managed.

You've worked on or led AI projects in some capacity

This is about decision-making, not implementation. You'll learn what to build and why, not how to code it.

No coding during the course; frameworks for thinking, not tutorials

Engineers who can build AI but want to master outcome engineering: knowing what to build, not just how

Building RAG, agents, or ML models? Let's get your demos into production! Learn the thinking that makes the difference.

Managers who need to evaluate AI/ML proposals, set realistic milestones, and know when to escalate

Evals aren't your product moat. A continuous improvement flywheel is.

AI Founder & Advisor to F500s | Ex-AWS

Amazon Web Services

Microsoft

University of Oxford

Aishwarya Naresh Reganti

June Cohort

Check out our free AI Evals Certification <a target="_blank" rel="noopener noreferrer nofollow" href="https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/ai_evals_for_everyone/README.md">here</a> (5000+) Learners!Most teams building AI products today know about evals and LLM judges, but they’re deeply confused about how to actually turn them into actionable improvement signals post production. Just throwing in LLM judges won’t magically fix your product. It won’t.<ul><li>This course shows how to use offline evals, online evals, and production monitoring to drive continuous improvement, based on real production experience.</li><li>We believe that going forward, a thoughtfully designed data flywheel will be the moat for AI applications. This course shows you how to build it.</li><li>This course is for people who’ve already built AI systems and are stuck with evals that are noisy, expensive, or uselessIf you need something more foundational, check out our top-rated flagship<a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/aishwarya-kiriti/genai-system-design"> enterprise AI course</a> taken by over 1500+ builders and leaders.</li><li>For questions or bulk enrollments please email problemfirst.ai@gmail.com</li><li>We follow a flipped-classroom format with async lecture content and meet twice a week for office hour style sessions to optimize two-way/interactive live time.</li></ul>

Move beyond one-time evals to continuous improvement flywheels for AI products

Understand what evals actually mean and why it’s misunderstood

Build a pre-deployment evaluation foundation from scratch

Choose the right types of metrics for the system you’re building

Monitor in production and close the improvement loop

You should have built small AI applications before and be familiar with concepts like RAG, MCP, and tool use.

A good understanding of AI system design

The course includes optional Python assignments, you're free to use coding agents, but basic coding skills are recommended

Working knowledge of Python/Coding (Optional)

Software/AI Engineers, Strategists, Data Professionals, Solution Architects and Consultants looking for systematic evaluation practices

Business Leaders and Product Managers seeking to gain the technical understanding of AI Product Lifecycle and intentional iteration

Founders &amp; teams stuck at systematic evaluations and monitoring, unsure how to turn signals into real product improvements.

This course is a comprehensive, hands-on journey into the world of AI, designed to equip learners with the skills to build & manage AI App

Cohort 9

Cohort 10

CEO & Founder, Decoding Data Science

Mohammad Arshad Ahmad


 AI mentor with 20+ years experience, creator of top AI programs helping careers

Cohort 3

In this course, students will gain hands-on experience with cutting-edge AI tools, frameworks, and methodologies, empowering them to build and deploy real-world applications. From mastering foundational concepts to implementing advanced generative AI models and MLOps pipelines, learners will develop practical skills that are in high demand across industries. With personalized mentorship, collaborative projects, and a strong focus on career outcomes, this course ensures students are fully equipped to excel in AI-driven roles and lead innovation in their fields. Use code SCHOLARSHIP code to get 50 % To get access to the only SELF-PACED course to access the recording use code SELFPACED to get it for $599 Any questions regarding this program book free One on One with me https://topmate.io/mohamad_arshad

Master AI tools, build real-world projects, and transform into an AI leader

✅ Outcome 1: Design Production-Grade AI Systems

✅ Outcome 2: Build & Deploy AI Apps End-to-End

Aspiring AI ProfessionalsThis course is designed for students, recent graduates, and early-career professionals who want to break into AI a

Mid-Career SwitchersIdeal for professionals from adjacent fields such as software engineering, IT, or business analytics who are looking to

AI Enthusiasts and EntrepreneursPerfect for tech enthusiasts, startup founders, and business leaders who want to integrate AI into their ve

AI Fundamentals

Apply AI in your role

Career Development

AI Fundamentals

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AI Fundamentals

Career development

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AI Fundamentals

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AI Fundamentals

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AI Fundamentals

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AI Fundamentals

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