Build AI Agents
Switch to AI/ML/DS
13 weeks (8 weeks core content + 5 weeks domain-specific capstones)
60+ hours of live training with FAANG+ experts
3 Live Guided Projects, 2 Capstone Projects
AI Engineering centric approach with Python-based frameworks for Software Engineers
Use-case centric approach with No-Code/Low-Code platforms for Tech Managers & other tech and product professionals
Senior FAANG and Tier-1 TPMs, AI Leads, and Software Engineers.
Foundations of Agentic AI, Multi-Agent Financial Systems, Optimization Strategies for AI Agents, End-to-End Capstone Projects
Additional FAANG+ interview preparation for AI-enhanced TPM roles
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 the AI tools and strategies that matter most — including RAG systems, AI API integration, LLM deployment, risk management, and AI program execution.
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.
*TPM interview prep is available with EdgeUp
*TPM 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.
Simplify data analysis by allowing users to generate insights from datasets using natural language inputs, eliminating the need for complex queries or coding. The system will integrate a robust data pipeline to load CSV files into an SQL database using the LangChain toolkit to connect with the database. The project utilizes SQL, Python, LangChain, and Streamlit, with plans to expand to other databases and BI tools.
Build Mira an agentic AI assistant that generates high level project plans from documents like scope briefs and risk assessments and auto produces weekly status reports by pulling live data from Trello. Designed for Nexora’s overloaded TPMs Mira reduces manual planning and reporting effort improves risk visibility and keeps AI adoption projects like ABCDE Ltd’s on track using grounded inputs human in the loop review and clear productivity metrics.
Design and implement CalendarMate, an Agentic AI assistant built on the low-code platform n8n to streamline meeting scheduling, consolidate meeting notes, summarize daily emails, and provide a quick activity overview. By integrating with multiple calendars and communication tools, CalendarMate resolves conflicts, improves productivity, and reduces missed meetings. You will also create a comprehensive program charter outlining objectives, scope, success metrics, risks, and a rollout plan.
Choose from one of 10 Capstone Projects.
Build Mira an agentic AI assistant that generates high level project plans from documents like scope briefs and risk assessments and auto produces weekly status reports by pulling live data from Trello. Designed for Nexora’s overloaded TPMs Mira reduces manual planning and reporting effort improves risk visibility and keeps AI adoption projects like ABCDE Ltd’s on track using grounded inputs human in the loop review and clear productivity metrics.
Design and implement CalendarMate, an Agentic AI assistant built on the low-code platform n8n to streamline meeting scheduling, consolidate meeting notes, summarize daily emails, and provide a quick activity overview. By integrating with multiple calendars and communication tools, CalendarMate resolves conflicts, improves productivity, and reduces missed meetings. You will also create a comprehensive program charter outlining objectives, scope, success metrics, risks, and a rollout plan.
Automate risk assessment for large-scale AI/ML programs by building a system that includes agents for scanning project documents, tracking dependencies, and suggesting mitigation strategies. Built with LangChain, CrewAI, OpenAI function calling, and RAG-based retrieval, it will ensure proactive risk management.
Automate workload balancing and developer resource forecasting by creating an agentic system that will analyze Jira and GitHub activity, predict bandwidth constraints, and integrate hiring needs with sprint planning. Using LangChain, CrewAI, and OpenAI embeddings, it optimizes engineering resource allocation.
+ 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:
How is this different from a general AI or ML course?
This course focuses on building and deploying autonomous AI agents using low-code and no-code tools, specifically for enterprise program management — not on deep ML theory.
Do I need a background in AI or machine learning to join this course?
No. The course is designed to be accessible to TPMs with no prior AI or ML experience. It starts with foundational concepts and progressively builds up to advanced topics.
What is the duration and structure of the course?
The course runs for 13 weeks: 8 weeks of core modules and 5 weeks of domain-specific learning and capstone projects.
What kind of projects will I build in the course?
How do Capstone Projects help my career?
Capstone Projects are designed with FAANG+ hiring managers in mind. Over 67% of hiring managers now demand to see practical know-how rather than certification or theoretical understanding. They’re reviewed for scalability, robustness, and relevance—showcasing your readiness for AI-enhanced roles
How does this course help me land a FAANG+ job?
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. Bonus content and interview preparation sessions are available for those who want to dive deeper.
Who are the instructors?
All our instructors are current or former FAANG+ professionals with deep expertise in Generative AI, LLMs, and AI/ML.
What tools and platforms will I learn?
You’ll work with tools like LangChain, AutoGen, CrewAI, LangGraph,n8n, Python, Streamlit, and more.
How is this different from a typical AI bootcamp?
This program goes beyond generic AI or prompt engineering training. It is designed for TPMs who want to lead AI implementation—not just build models—focusing on deploying intelligent systems into real-world programs.
What support do I get during the course?
You get access to:
What are the career outcomes or placement support offered?
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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