Data-Science

Why I took this course I wanted a systems lens on Artificial Intelligence (AI) agents: when to use them, how to scope autonomy, and how to operate them in production under real constraints (cost, latency, reliability, compliance). I needed a repeatable method to go from a business problem → agent design → evaluation → rollout, not just a prompt that works on Friday and fails on Monday. The weekly Chai & AI (tea-and-AI) sessions were the best hook: people from varied backgrounds brought real problems, unpacked buzzwords, and shared concrete patterns—immediately useful for day-to-day work....

No More Data Gatekeepers: How We’re Making Analytics Accessible to Everyone In the modern enterprise, we’re told that data is our most valuable asset. But for many, it remains locked away, accessible only to a select few. The process is all too familiar: a question arises about a campaign, a ticket is filed, and days—or even weeks—later, a report arrives. By then, the opportunity to act may have already passed....