Build AI Agents
Switch to AI/ML/DS
Gain mentorship and practical insights from top FAANG+ experts who are actively shaping the future of Agentic AI.
Master critical Agentic AI skills without getting lost in noise — at a pace that fits your schedule and leadership responsibilities.
Cover everything from foundational Agentic AI concepts to advanced enterprise-grade AI workflows, automation, and decision-making systems.
Focus on tools and strategies that matter — including sprint optimization agents, engineering analytics bots, cost monitoring agents, and roadmap planners.
Tackle practical challenges through live guided projects and domain-specific capstones — including stakeholder management automation and resource allocation agents.
With an NPS of 55 and an average learner rating of 4.75+, our structured, hands-on approach consistently earns high praise from tech professionals like you.
*EM interview prep is available with EdgeUp
*EM interview prep is available with EdgeUp
Build a powerful AI agent without needing to write extensive code. Using n8n, a popular workflow automation tool, you’ll learn how to design an AI agent that can handle stock analysis, provide financial insights, and much more — all with minimal coding effort.
By leveraging n8n’s intuitive interface, you’ll integrate multiple services like Telegram, OpenAI, and Airtable to build an intelligent, scalable AI agent that automates tasks, analyzes data, and delivers real-time insights.
Develop a real-world, multi-agent healthcare agents (HealthSense AI) using low-code tool like n8n automation platform. This is designed to help participants leverage the power of Large Language Models (LLMs) and no-code orchestration for building context-aware, modular healthcare workflows that directly address real patient and provider needs.
You will architect and deploy AI-powered agents—without writing code—that can book doctor appointments, compare hospitals, route emergencies, and provide diagnostic recommendations. The skills you develop will prepare you to revolutionize healthcare access through scalable, intelligent automation.
Build a powerful AI agent without needing to write extensive code. Using n8n, a popular workflow automation tool, you’ll learn how to design an AI agent that can handle stock analysis, provide financial insights, and much more — all with minimal coding effort.
By leveraging n8n’s intuitive interface, you’ll integrate multiple services like Telegram, OpenAI, and Airtable to build an intelligent, scalable AI agent that automates tasks, analyzes data, and delivers real-time insights
Develop a real-world, multi-agent healthcare agents (HealthSense AI) using low-code tool like n8n automation platform. This is designed to help participants leverage the power of Large Language Models (LLMs) and no-code orchestration for building context-aware, modular healthcare workflows that directly address real patient and provider needs.
You will architect and deploy AI-powered agents—without writing code—that can book doctor appointments, compare hospitals, route emergencies, and provide diagnostic recommendations. The skills you develop will prepare you to revolutionize healthcare access through scalable, intelligent automation.
Projects are subject to change as per industry inputs. Choose from one of 3 Capstone Projects.
This project equips Engineering Managers with an AI-powered multi-agent system that transforms complex BRDs into structured engineering plans and technical designs. Using n8n for orchestration, LLMs for parsing and generation, and a user-friendly UI, learners build agents for planning, scheduling, architecture, PoC scoping, and tech stack recommendations. The solution streamlines project initiation, enforces standardization, and accelerates decision-making, enabling EMs to produce stakeholder-ready artifacts quickly and efficiently.
This Project enables Engineering Managers to gain real-time visibility and insights into the hiring funnel using a multi-agent intelligence system. Built with n8n orchestration and LLM-driven analysis, agents track sourcing quality, rejection trends, panel workloads, and offer declines. The system generates actionable recommendations, highlights bottlenecks, and presents metrics via a dashboard-style UI. By standardizing insights and automating interventions, learners build tools that enhance hiring efficiency, improve candidate experience, and accelerate role closures.
This project empowers Engineering Managers to build a multi-agent system that automates team surveys, extracts insights, and drives actionable improvements in culture, learning, and career growth. Using n8n orchestration, LLM-powered survey generation, adaptive feedback logic, and dashboard-style interfaces, learners design agents for survey cycles, sentiment analysis, action recommendations, and follow-up tracking. The system helps EMs foster engagement, track progress over time, and translate team feedback into tangible outcomes for morale, retention, and performance.
Projects are subject to change as per industry inputs. Choose from one of 3 Capstone Projects.
This project equips Engineering Managers with an AI-powered multi-agent system that transforms complex BRDs into structured engineering plans and technical designs. Using n8n for orchestration, LLMs for parsing and generation, and a user-friendly UI, learners build agents for planning, scheduling, architecture, PoC scoping, and tech stack recommendations. The solution streamlines project initiation, enforces standardization, and accelerates decision-making, enabling EMs to produce stakeholder-ready artifacts quickly and efficiently.
This Project enables Engineering Managers to gain real-time visibility and insights into the hiring funnel using a multi-agent intelligence system. Built with n8n orchestration and LLM-driven analysis, agents track sourcing quality, rejection trends, panel workloads, and offer declines. The system generates actionable recommendations, highlights bottlenecks, and presents metrics via a dashboard-style UI. By standardizing insights and automating interventions, learners build tools that enhance hiring efficiency, improve candidate experience, and accelerate role closures.
This project empowers Engineering Managers to build a multi-agent system that automates team surveys, extracts insights, and drives actionable improvements in culture, learning, and career growth. Using n8n orchestration, LLM-powered survey generation, adaptive feedback logic, and dashboard-style interfaces, learners design agents for survey cycles, sentiment analysis, action recommendations, and follow-up tracking. The system helps EMs foster engagement, track progress over time, and translate team feedback into tangible outcomes for morale, retention, and performance.
FAANG+ Instructors to Train You 
FAQs
What is Agentic AI, and how is it different from traditional AI?
Agentic AI focuses on autonomous systems that operate proactively to achieve goals using LLMs and other tools, without constant human intervention. Unlike traditional AI, which is often reactive and generally requires explicit instructions for each task, Agentic AI understands its environment, thinks through the goals and how to achieve them, makes decisions, takes actions, learns from its experiences, and adapts its behavior over time.
What are the practical applications of Agentic AI?
Applications of Agentic AI include:
What does this course teach?
This course teaches Engineering Managers how to integrate Agentic AI into engineering workflows to drive automation, efficiency, and strategic decision-making.
Do I need prior AI or ML experience to enroll in this course?
No, our Applied Agentic AI Program for Engineering Managers is beginner-friendly and designed for EMs from diverse technical backgrounds. A Python crash course is included.
What kind of projects will I build in the course?
You’ll build hands-on projects like an AI agent for stock analysis, a multi-agent healthcare system, an automated data insights generator, using python and low-code platform like n8n.
Will I learn how to lead AI teams?
Yes. Specialized sessions focus on technical guidance, AI leadership, ROI evaluation, and managing AI/ML professionals.
How does this course help me land a FAANG+ job?
Through live sessions led by FAANG+ practitioners, FAANG-focused interview prep, and mock interviews with hiring managers and tech leads. You’ll also build a compelling portfolio with capstone projects reviewed by mentors from companies like Google, Amazon, and Meta.
How much time do I need to commit weekly?
Expect around 10 hours of learning per week , covering live sessions, project work, and domain-specific learning. The structure is of 14 weeks—9 weeks of core curriculum, 5 weeks of domain-specific Capstone Projects, with live sessions and peer feedback.
Who are the instructors?
All our instructors are current or former FAANG+ Engineering Leaders with deep expertise in Generative AI, LLMs, and AI/ML.
What tech stack and tools will I learn?
You’ll work with LangChain, LangGraph,n8n, Streamlit, Pinecone, LlamaIndex, FastAPI, and more.
What support do I get during the course?
You get access to:
How is this different from other AI or ML courses?
This course focuses on real-world engineering use cases, with no-code/low-code tools, leadership development, and Agentic AI—not abstract theory or deep ML.
What happens if I miss a live session?
All live sessions are recorded and accessible on-demand. You can catch up anytime and even rewatch for revision.
Is there a payment plan?
Yes! We offer multiple financing options to make the course more accessible to working professionals.
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