AI is creating new possibilities for businesses, but turning promising experiments into practical, production-ready solutions requires more than just building a model. It involves working with the right data, selecting appropriate techniques, evaluating performance, and designing systems that can address real-world challenges reliably.
Join this webinar to explore what it takes to move AI systems from pilot projects to production. Discover the key considerations involved in developing, evaluating, and deploying AI solutions, and understand how technologies such as Machine Learning and Agentic AI are shaping the next generation of intelligent systems.
Agenda for the session
- Understanding the AI development journey
- From AI experimentation to implementation
- Key challenges in scaling AI adoption
- Live Q&A session
About Speakers
Angel Das
Senior Consultant, IQVIA Asia Pacific
Angel Das is an advanced analytics professional who helps companies find solutions for various problems through a mix of business, technology, and math on organizational data. He has experience establishing relationships with Fortune 500 clients in a white box and collaborative manner to improve the art of problem-solving for constantly shifting and ill-defined business problem.
MIT Professional Education's Applied AI and Data Science Program
The Applied AI and Data Science Program , offered by MIT Professional Education, provides a structured path from data fundamentals and Machine Learning models to Generative AI, Agentic AI, and multi-agent workflows using LangGraph, RAG, n8n, and Claude. The program is designed for experienced technology professionals who want to build and evaluate AI systems for their organizations, as well as for professionals looking to transition into high-growth data and AI roles.
