The Mahesh Yadav Institute focuses on quality over quantity and is passionate to educate the next generation of AI product leaders. We only offer 4 cohorts throughout the year and limit each cohort to 40-50 students to maximize the 1:1 mentoring time you get from Mahesh.

📚 We are part of Maven's BUILDWITH AI series, where only the Top instructors in AI are selected. In terms of leadership style, Mahesh is a servant leader. He believes in giving back and wants to help you to become #1 in the AI/ML space.

🚀 Why Join Us?

For Aspiring AI Leaders:

- Access 5 live sessions (90 mins each) covering advanced AI/ML strategies.

- Gain hands-on experience through 5 lab sessions (60-90 mins) – crucial if you want to stand out as an AI Product Manager.

- Early access to essential course materials to jumpstart your learning journey.

- Lifetime support: Whether you're building your own AI company, seeking mentorship, or transitioning to an AI PM role, Mahesh will continue to guide you post-graduation.

We believe this is only achievable in a smaller class setting and genuine care for students in their career journey post-graduation.

👨‍💻 𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗜𝗡𝗦𝗧𝗥𝗨𝗖𝗧𝗢𝗥

Mahesh Yadav worked as GenAI PM lead at Various MAANG-level companies. He has over 20 years of experience in AI/ML Product management and engineering, specializing in deploying large language model (LLM) based services and enhancing AI infrastructure at companies like AWS AI (Bedrock), Meta (PyTorch and Feed), and Microsoft Azure AI. Mahesh is the original product builder for AWS Bedrock GenAI services, and he grew the platform's customers from zero to 10k in 8 months. In addition, he optimized Pytorch at Meta by moving it from a single cluster training platform to a multi-cluster training platform and expanded the feed models from Billion to Trillion in scale to increase feed CTR.

Mahesh is on a mission to educate the next generation of AI/Ml product managers. He has taught 1000s of students in his Meta internal channel course, and 5 cohorts at PMExercises.Mahesh's vision is to educate the next wave of AI product managers by sharing his successes and mistakes—ensuring you're prepared for the challenges ahead.

💡 𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗢𝗨𝗥𝗦𝗘

Drawing from my experiences developing ML/AI products and working at leading companies like Facebook, AWS etc, I've observed a critical gap :

"Aspiring AI PMs struggle in the AI space due to a lack of understanding of AI/PM product basics, technical concepts, or the absence of a hands-on project"t

In this course, I will share in-depth topics that will truly help set you apart for AI ML space, and rehash what you already know. In addition, we will provide a hands-on lab to build your AI product portfolio.

I have designed this course based on my two decades of experience at Microsoft, Meta and Amazon to not only provide deep insights into AI PM fundamentals but also to focus on the technical aspects and practical applications needed in the AI field which will prepare you for the real-life interview settings, and your AI PM career.

Throughout the course, you will have practical lab sessions to help you to understand the tradeoff you have to make as an AI product manager.

Furthermore, you will also develop effective product requirement documents (PRDs), and embark on creating your first AI-driven product with a talented community of highly driven individuals, guided by me.

Key AI PM Technical Knowledge Covered

(This is a small sample of what we will go through in class. AI is a rapidly changing field. What sets me apart from other instructors is I am in the core GenAI team working with the core tech, so I can continue to bring in the latest concepts and industry insights for each cohort)

• Basic AI Concepts (e.g. Neural Networks, Transformers, Diffusion)

• Real-world examples of ML/AL execution and tradeoffs

• Special focus on GenAI, its applications, and deployment with technical deep-dive

• Types of AI Models and Applications

• How to evaluate the success of GenAI models and systems

• AI/ML Stacks

• Advance knowledge and session on AGI's

• LLM-Powered Agents and Agent Creation

• Prompt Engineering

• Prompting Techniques (e.g. Zero-shot, chain of thoughts)

• Fine-tuning ML models (e.g. PEFT, LoRA) & RLHF

• Retrieval Augmented Generation (RAG) & Retrieval Augmented Fine-Tuning (RAFT)

💡 COURSE PREREQUISITES

This course requires a traditional PM or equivalent background, but we have cohort members from other backgrounds in design and ML engineering who have proved to be a great fit too. Contact us if you have questions if this course will be a good fit for you.