Note: This course is an independent offering and is not affiliated with, endorsed by, or related to the instructors' current or past employers.

Agentic AI or AI systems capable of operating with some degree of autonomy, is transforming how we interact with technology. In the coming years, most software systems will integrate AI agents to enhance their capabilities. This shift will drive a growing demand for professionals who can move beyond surface-level understanding and apply AI effectively to solve real business challenges while navigating practical constraints.

This course focuses on practical AI agent development, covering key usage paradigms such as workflow agents, integrating RAG/retrieval components, autonomous agents, and fine-tuning—all with a strong emphasis on real-world applications.

Instead of just explaining "what" these techniques are, we’ll explore "when" and "how" to use them, equipping you to make informed, business-driven AI decisions.

⛳ What Makes This Course Unique

Solving Real Enterprise Challenges, Not Just Concepts

While most courses stop at teaching tools and frameworks, this course goes further by focusing on solving real-world business problems. You’ll tackle practical constraints like cost, scalability, latency, and performance, learning to design AI solutions tailored to real use cases that deliver value.

Participate in Weekly Enterprise Use-Case Workshops with Peers

All content will be recorded and available for async viewing. Each week, we’ll have team workshops to discuss real-world business use cases that can be tackled using the concepts covered that week, along with any challenges we encounter.

Hands-On Product Development

You’ll build a real-world agentic product from scratch (low code options available). Our tutorials will guide you through creating your own Perplexity (Agentic search system), giving you practical experience with application techniques.

Collaborative Team Workshops

Experience what it’s like to solve a business problem in a real-world setting. In a collaborative workshop, you’ll work with others to design and develop solutions, simulating how teams take AI projects from 0 to 1. 

Capstone Project

Learn how to connect cutting-edge research with real-world applications. For the capstone, you’ll use our curated list of the latest research papers to design and implement solutions for practical business use cases.

☕ Weekly Chai & AI Sessions with Our Problem-First Community

Join optional weekly sessions during the course where we discuss the latest AI developments, their impact on enterprises, and what they mean in practice. We bring in guest speakers, including AI practitioners, industry leaders, founders, and VCs for AMA sessions, along with deep dives into research and hands-on workshops to bridge theory with real-world applications.

Guest Lectures from Industry Experts

We believe in learning from practitioners who have built and deployed real AI solutions in the enterprise—not just talkers, but doers. Our past cohort guest lectures have featured leaders who drive AI adoption at scale, including:

Aman Khan – Director of Product, LLM @ Arize AI

Doneyli De Jesus – Principal AI Architect @ Snowflake

Jayeeta Patatunda – Director, AI CoE @ Fitch Ratings

We aim to bring many more industry leaders in future cohorts, ensuring you learn from the best in the field.

🫨🫨🫨The Biggest Advantage! (Lifetime access to future cohort material)

AI moves fast, and staying ahead means continuous learning. That’s why all students get lifetime access to the latest AI material from all future cohorts—no extra fees, no outdated content. You’ll always have access to latest cohorts lecture recordings and reading materials, incorporating the latest model updates (like reasoning models currently), emerging techniques, industry shifts, and best practices.

This is your one-stop learning hub—no need to keep signing up for new AI courses.

New Concepts Coming to the May 2025 Cohort:

Reasoning Models – A full module on when, how, and why to use them

MCP & Agentic Apps – Building agentic applications using MCP

Agent Evaluations – Methods and best practices for assessing agents

Agent Architecture Breakdown – Deep dive into popular agents like NotebookLM, Deep Research, and potential architectures

🙌 Plus, top students get lifetime access to our Chai & AI community sessions and in-person meetups, where they can dive into deep discussions, network with top industry professionals, and gain exclusive insights straight from the frontlines of AI.

❌ Who This Course Is Not For

For Those Who Have Already Deployed Gen AI in Enterprise: This course is designed as an applied foundations course for enterprise AI with only basic Python as a prerequisite and no ML background required. If you’re already familiar with deploying AI systems, you won’t gain much from the core content. However, if you're looking to network and refine best practices, you're welcome to join.

Those Seeking Heavy Theoretical Knowledge: This course emphasizes applied learning and practical problem-solving, not deep dives into theoretical topics like transformer architecture, pre/post-training optimization, inference techniques, or alignment.

Those Who Have Never Coded Before: While we provide low-code options, this course assumes you have some coding experience. It’s not suitable for those who have never written or worked with even basic code.

Individuals Expecting Deep AI Research Focus: While we’ll cover cutting-edge techniques, this course is centered on applying AI to business problems, not research-heavy exploration.

Scaling and Ops Enthusiasts: This course does not focus heavily on scaling or operational aspects (i.e., LLMOps). Deployment will be covered at a high level, but not in-depth.