Every role today works with data: sales numbers, customer feedback, reports, emails, documents. Generative AI now makes it possible to analyse all of it, not just the neat rows in a spreadsheet. And with today’s no-code and AI-assisted coding tools, you no longer need to be a data scientist to put AI to work.
In this live session, we’ll show how AI handles both structured and unstructured data, how no-code and code tools each make AI accessible, and how professionals in any domain can apply Generative AI and Agentic AI to their own data at work.
Whether you’ve never written a line of code or you already work in Python, you’ll leave with a clear picture of what’s possible and where to start.
What you’ll learn
- Types of data and how Gen AI works with them: the difference between structured data (tables, transactions, sales figures) and unstructured data (documents, emails, reviews, images), and how Generative AI can analyse, summarise and draw insights from both.
- How no-code and code tools make AI accessible: what you can build with no-code tools like KNIME and n8n, what AI-assisted coding with tools like Codex and Claude adds, and how to choose the right approach for your role.
- Using Gen AI and Agentic AI on your domain’s data: practical examples of AI agents and workflows in areas like marketing, finance, operations, healthcare and HR, and how to identify the first use case in your own workplace.
Agenda for the session
- Structured vs unstructured data: how Gen AI works with both
- No-code and code tools that make AI accessible
- Using Gen AI and Agentic AI on your domain’s data
- Learning pathways with MIT and live Q&A
About Speakers
Peyman Hessari
Senior Data Scientist, ATB Financial
Peyman Hessari is a Senior Data Scientist at ATB Financial in Canada and an industry mentor for MIT Professional Education’s No Code AI program, delivered in collaboration with Great Learning. He helps professionals apply data science and AI to real-world business problems.
