Build AI Agents
Switch to AI/ML/DS
7 weeks
2 Live Guided Projects, 1 Capstone Project
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
FAANG and Tier-1 software engineers and architects, AI/ML leads, and AI/ML engineers.
This 7-week curriculum provides a structured journey from foundational GenAI concepts to advanced agentic AI development. It blends self-paced learning and live classes to cover Python for GenAI, LLM applications, agent building, optimization, and a hands-on capstone project.
Learn directly from FAANG+ experts, gaining practical insights and mentorship from industry leaders who are at the cutting edge of Agentic AI.
Apply AI in SWEs contexts like automated code reviews, intelligent DevOps workflows, and AI-powered debugging assistants.
Designed for working SWEs to master Agentic AI without disrupting work-life balance.
Apply your learning to real industry challenges, including building a healthcare AI assistant and developing a financial multi-agent advisory system, through two guided projects and a capstone project.
Master the full spectrum of Agentic AI, from foundational concepts to advanced, real-world applications—specializing in AI agent workflows and automation.
With an NPS of 55 and an average rating of 4.75+, our learners consistently praise our structured, hands-on approach to mastering Agentic AI.
Laying the Groundwork for AI-Driven Development (Self-paced)
Bonus Content: Hands-on with Generative AI Models (Self-paced with live assignment review)
Specialized Session #2: Building Effective Prompts and Configuration-Driven Apps (Self- paced)
Specialized Session #2: Building Effective Prompts and Configuration-Driven Apps (Self- paced)
Evaluation & Optimizing AI Agents: Performance & Cost Efficiency Capstone Project Initiation
Laying the Groundwork for AI-Driven Development (Self-paced)
Bonus Content: Hands-on with Generative AI Models (Self-paced with live assignment review)
Specialized Session #2: Building Effective Prompts and Configuration-Driven Apps (Self- paced)
Specialized Session #2: Building Effective Prompts and Configuration-Driven Apps (Self- paced)
Evaluation & Optimizing AI Agents: Performance & Cost Efficiency Capstone Project Initiation
Build an intelligent healthcare assistant with LangGraph for structured reasoning and medical knowledge integration. This agent handles patient queries, symptom assessment, and information retrieval through conversation. It features contextual memory, appointment scheduling, medication reminders, and personalized advice. Utilize LangGraph for decision trees, and RAG for medical knowledge retrieval. Tools include Python, LangGraph, Pinecone, and OpenAI APIs.
Develop a financial advisory system using LangGraph’s multi-agent architecture. Implement specialized agents for market analysis, portfolio management, risk assessment, and recommendations that work collaboratively. Use agent-to-agent communication, parallel tasks, and consensus mechanisms alongside ReAct and Chain-of-Thought prompting for transparent reasoning. Features include data visualization, investment strategies, and scenario planning. Build with LangGraph for orchestration, LangChain for tools, ChromaDB for vector storage, and Streamlit for dashboards.
Build an intelligent healthcare assistant with LangGraph for structured reasoning and medical knowledge integration. This agent handles patient queries, symptom assessment, and information retrieval through conversation. It features contextual memory, appointment scheduling, medication reminders, and personalized advice. Utilize LangGraph for decision trees, and RAG for medical knowledge retrieval. Tools include Python, LangGraph, Pinecone, and OpenAI APIs.
Develop a financial advisory system using LangGraph’s multi-agent architecture. Implement specialized agents for market analysis, portfolio management, risk assessment, and recommendations that work collaboratively. Use agent-to-agent communication, parallel tasks, and consensus mechanisms alongside ReAct and Chain-of-Thought prompting for transparent reasoning. Features include data visualization, investment strategies, and scenario planning. Build with LangGraph for orchestration, LangChain for tools, ChromaDB for vector storage, and Streamlit for dashboards.
Projects are subject to change as per industry inputs. Choose from one of 10 Capstone Projects.
Build an agentic system that automates DevOps workflows through four specialized agents: a Code Analyzer for security reviews, a CI/CD Monitor for deployment oversight, an Infrastructure Scaler for resource management, and an Incident Resolver for system diagnostics. Build it with LangChain, CrewAI, and OpenAI API and integrate with GitHub Actions, AWS Lambda, and containerization tools, while using vector databases and monitoring solutions.
Build an assistant that streamlines healthcare services through four specialized agents: a Symptom Checker for initial assessments, an Appointment Scheduler for EHR/EMR integration, a Medical FAQ Bot for patient queries, and an Insurance Advisor for claims guidance. Use LangChain, GPT-4, and healthcare APIs to create a system that offers comprehensive patient support while maintaining secure data management through VectorDB storage.
Build a comprehensive agentic system utilizing four specialized agents to protect applications: a Vulnerability Scanner for detecting common threats, a Code Security Analyzer for OWASP Top 10 compliance, a Log Analyzer for anomaly detection, and a Compliance Checker for regulatory standards. Use tools like LangChain, OpenAI GPT, and OWASP ZAP to ensure robust security through integrated monitoring and analysis.
Employ four specialized agents to streamline legal document processing: a Contract Analyzer for extracting key elements, a Compliance Checker for regulatory validation, a Case Law Researcher for finding precedents, and a Summary Generator for creating digestible content. Use LangChain, OpenAI, and OCR tools to offer comprehensive legal document analysis through an interactive interface.
Build a multi-agent system designed to automate supply chain processes, including inventory management, demand forecasting, and logistics tracking. The system consists of four agents: a demand forecaster using time-series ML models, an inventory manager analyzing stock levels, a logistics tracker monitoring shipments, and a procurement assistant optimizing supplier contracts. Leverage Python, TensorFlow, XGBoost, LangChain, OpenAI API, SQL/NoSQL databases, and visualization tools like Streamlit in this project.
Enhance software development with an AI-powered pull request (PR) reviewer bot that automates code reviews using Large Language Models (LLMs). This bot provides detailed feedback, identifies bugs, security vulnerabilities, and coding violations, and suggests best practices to streamline the code review process. It improves efficiency and code quality while assisting human reviewers. Integrate with GitHub/GitLab for seamless operation and use models like GPT-4 or Hugging Face Transformers for accurate code analysis. Build with React or Streamlit, and deploy using Docker and AWS for smooth execution.
Enhance call center operations with an AI-powered summarization bot that leverages Large Language Models (LLMs) to generate concise summaries of customer interactions. This tool provides quick overviews, improving decision-making and customer service efficiency. The bot automates manual summary writing, ensuring consistent and accurate records. Integrate with GPT-4, Cohere, or Hugging Face Transformers for superior NLP capabilities. Build the interface with React or Streamlit, and deploy using Docker and AWS for seamless operation.
Streamline email communication with an AI-powered Email Generator App that leverages Large Language Models (LLMs) to generate professional and contextually accurate email drafts. The app provides quick, reliable suggestions based on user inputs, ensuring high accuracy and relevance. It supports customization and personalization, enhancing the efficiency of email management. Integrate with models like GPT-4, Cohere, or Hugging Face Transformers for superior performance. Build the interface with React or Streamlit, and deploy the application using Docker and AWS for seamless operation.
Streamline the hiring process with an AI-powered assistant that automates resume screening and scoring using large language models (LLMs). This tool evaluates resumes against job descriptions, identifying strengths, weaknesses, and alignment with role requirements. It enhances ATS platforms by providing actionable feedback and recommendations to find the best-fit candidates. Integrate with tools like GPT-4, Gemini Pro, and LangChain for seamless operation. Build a user-friendly interface using React, Node.js, and MongoDB, and deploy it on the cloud with Docker and AWS.
Work on personal or professional projects of your choice. BYOP offers mentorship, structured guidance, and feedback to ensure projects are aligned with industry standards and best practices. It fosters creativity, innovation, and real-world problem-solving, enabling participants to build impactful solutions. You will receive guidance on selecting the right tools and frameworks based on project requirements.
Projects are subject to change as per industry inputs. Choose from one of 10 Capstone Projects.
Build an agentic system that automates DevOps workflows through four specialized agents: a Code Analyzer for security reviews, a CI/CD Monitor for deployment oversight, an Infrastructure Scaler for resource management, and an Incident Resolver for system diagnostics. Build it with LangChain, CrewAI, and OpenAI API and integrate with GitHub Actions, AWS Lambda, and containerization tools, while using vector databases and monitoring solutions.
Build an assistant that streamlines healthcare services through four specialized agents: a Symptom Checker for initial assessments, an Appointment Scheduler for EHR/EMR integration, a Medical FAQ Bot for patient queries, and an Insurance Advisor for claims guidance. Use LangChain, GPT-4, and healthcare APIs to create a system that offers comprehensive patient support while maintaining secure data management through VectorDB storage.
Build a comprehensive agentic system utilizing four specialized agents to protect applications: a Vulnerability Scanner for detecting common threats, a Code Security Analyzer for OWASP Top 10 compliance, a Log Analyzer for anomaly detection, and a Compliance Checker for regulatory standards. Use tools like LangChain, OpenAI GPT, and OWASP ZAP to ensure robust security through integrated monitoring and analysis.
Employ four specialized agents to streamline legal document processing: a Contract Analyzer for extracting key elements, a Compliance Checker for regulatory validation, a Case Law Researcher for finding precedents, and a Summary Generator for creating digestible content. Use LangChain, OpenAI, and OCR tools to offer comprehensive legal document analysis through an interactive interface.
Build a multi-agent system designed to automate supply chain processes, including inventory management, demand forecasting, and logistics tracking. The system consists of four agents: a demand forecaster using time-series ML models, an inventory manager analyzing stock levels, a logistics tracker monitoring shipments, and a procurement assistant optimizing supplier contracts. Leverage Python, TensorFlow, XGBoost, LangChain, OpenAI API, SQL/NoSQL databases, and visualization tools like Streamlit in this project.
Enhance software development with an AI-powered pull request (PR) reviewer bot that automates code reviews using Large Language Models (LLMs). This bot provides detailed feedback, identifies bugs, security vulnerabilities, and coding violations, and suggests best practices to streamline the code review process. It improves efficiency and code quality while assisting human reviewers. Integrate with GitHub/GitLab for seamless operation and use models like GPT-4 or Hugging Face Transformers for accurate code analysis. Build with React or Streamlit, and deploy using Docker and AWS for smooth execution.
Enhance call center operations with an AI-powered summarization bot that leverages Large Language Models (LLMs) to generate concise summaries of customer interactions. This tool provides quick overviews, improving decision-making and customer service efficiency. The bot automates manual summary writing, ensuring consistent and accurate records. Integrate with GPT-4, Cohere, or Hugging Face Transformers for superior NLP capabilities. Build the interface with React or Streamlit, and deploy using Docker and AWS for seamless operation.
Streamline email communication with an AI-powered Email Generator App that leverages Large Language Models (LLMs) to generate professional and contextually accurate email drafts. The app provides quick, reliable suggestions based on user inputs, ensuring high accuracy and relevance. It supports customization and personalization, enhancing the efficiency of email management. Integrate with models like GPT-4, Cohere, or Hugging Face Transformers for superior performance. Build the interface with React or Streamlit, and deploy the application using Docker and AWS for seamless operation.
Streamline the hiring process with an AI-powered assistant that automates resume screening and scoring using large language models (LLMs). This tool evaluates resumes against job descriptions, identifying strengths, weaknesses, and alignment with role requirements. It enhances ATS platforms by providing actionable feedback and recommendations to find the best-fit candidates. Integrate with tools like GPT-4, Gemini Pro, and LangChain for seamless operation. Build a user-friendly interface using React, Node.js, and MongoDB, and deploy it on the cloud with Docker and AWS.
Work on personal or professional projects of your choice. BYOP offers mentorship, structured guidance, and feedback to ensure projects are aligned with industry standards and best practices. It fosters creativity, innovation, and real-world problem-solving, enabling participants to build impactful solutions. You will receive guidance on selecting the right tools and frameworks based on project requirements.
+ Instructors to Train You
FAQs
What is Agentic AI, and how is it different from traditional AI?
Agentic AI refers to AI systems that act as autonomous “agents” capable of reasoning, planning, and executing tasks independently or in collaboration with other agents. Unlike rule-based systems, these agents can orchestrate complex workflows using LLMs, adapt over time, and integrate with real-world tools—making them more powerful and practical for business and tech applications.
What are the practical applications of Agentic AI?
Applications of Agentic AI include:
What makes this course unique compared to general LLM or GenAI courses?
Unlike most courses that focus only on LLM usage or prompting, this one teaches end-to-end agentic system design, multi-agent orchestration, tool integration, and real-world deployment specifically for software engineering—all guided by FAANG+ instructors.
Do I need prior AI or ML experience to enroll in this course?
No, the course starts with Python fundamentals and AI basics, gradually progressing to LLM frameworks, model fine-tuning, and multi-agent AI. All necessary concepts will be covered throughout the program.
What kind of projects will I build in the course?
You’ll build 2 live guided projects and 1 capstone project of your choice, such as a security auditing system or an AI-driven project manager—equipping you with portfolio-ready assets.
How much time do I need to commit weekly?
On average, participants should dedicate:
Who are the instructors?
You’ll learn from current and former FAANG+ professionals and AI leaders who’ve built real Agentic AI systems. Instructors include GenAI leads, ML architects, senior engineers, and AI software engineers from Google, Amazon, and more.
What tech stack and tools will I learn?
You’ll gain hands-on experience with cutting-edge tools, including:
What support do I get during the course?
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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