Learn Agentic AI & Build Agents That Work for You

Build systems that generate, reason, and collaborate across tasks—just like modern software demands.
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Course Highlights

Best Suited for:

  • Software Engineers (Backend, Frontend, Fullstack, Test)
  • AI Enthusiasts with Software Engineering/Coding Backgrounds

Duration

14 weeks

Course hours

  • 60+ hours of live interaction with industry experts from top tech companies
  • 30+ hours of expert-guided live hands-on projects
  • 21+ hours of power-packed specialized sessions 

Projects

3 Guided Projects, 10 Capstone Projects to choose from

Instructors

Generative & Agentic AI practitioners from FAANG and other global Tier 1 companies

Curriculum coverage

Autonomous AI Agents, Multi-Agent Systems, Agentic AI Strategies, RAG, LLM Orchestration, real-world application of Agentic AI, and more

Get your copy of the course brochure

Turbocharge Your Career with Gen AI

  • Full details of the curriculum
  • Hands-on Guided Projects and Capstone Projects
  • Career Support Services

Get your copy of the course brochure

Turbocharge Your Career with Gen AI

  • Full details of the curriculum
  • Hands-on Guided Projects and Capstone Projects
  • Career Support Services
Average package for alumni
100 LPA
Careers transformed
0 K+
Average ROI on course price
0 x

20+ Tools & Tech You’ll Learn

Why Choose Our Transformative GenAI Software Pathway:

Learn from 600+ Mentors from FAANG+ Companies

Get real-world guidance from experienced engineers who’ve built AI systems at Google, Amazon, Microsoft, and more.

Flexible Format Tailored for Working Engineers

Designed to help full-time software professionals upskill without affecting your job or personal schedule.

Covers the Full Agentic AI Stack

Build strong foundations and master advanced workflows—covering everything from GenAI basics to multi-agent orchestration and deployment.

Focused on Developer-Centric Use Cases

Learn how to use AI for debugging, CI/CD automation, code review, and tool creation—built specifically for software engineering roles.

Project-Driven Curriculum with Real Use Cases

Build agents for real-world applications in healthcare and finance through two guided projects and a capstone project that showcases your skills.

Trusted by 25K+ Engineers With Proven Outcomes

Backed by 25,000+ career transitions, a learner-rated NPS of 55, and an average course rating of 4.75+ across past cohorts.

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Detailed Curriculum of Our Transformative GenAI Pathway For Software Engineers

Specialized Session 1: Laying the Groundwork for AI-Driven Development
Fundamentals of Agentic AI Specialized Session 2: Building Effective Prompts and Configuration-Driven Apps (Self- paced)
Build Your First AI Agent
Building Applications with LLMs & Agents - Lite
Building Applications with LLMs & Agents - Advanced Specialized Session 3: Innovating with Multi-Agent Systems and Specialized Models (Self-paced)
LLM Architecture & Pre-training LLMs Specialized Session #4: Harnessing LLM Frameworks for Real-World Development (Self-paced)
Build Your Advanced Multi-Agent System
Live Guided Project: Call Center Conversational Audio Bot with GenAI Specialized Session #5: From Development to Deployment: Scaling and Debugging AI Models (Self-paced)
Evaluation & Optimizing AI Agents: Performance & Cost Efficiency Specialized Session 6: Managing Data Pipelines and Integrating APIs (Self-paced)
Designing Robust and Scalable AI Systems for Modern Applications
Capstone Project
Specialized Session 1: Laying the Groundwork for AI-Driven Development
3 sessions Bonus Content: Self-Paced
Python Fundamentals Refresher
Evolution of GenAI
Hands-on with Generative AI Models
ML Foundations

Detailed Curriculum of Our Transformative GenAI Pathway For Software Engineers

Specialized Session 1: Laying the Groundwork for AI-Driven Development
Fundamentals of Agentic AI Specialized Session 2: Building Effective Prompts and Configuration-Driven Apps (Self- paced)
Build Your First AI Agent
Building Applications with LLMs & Agents - Lite
Building Applications with LLMs & Agents - Advanced Specialized Session 3: Innovating with Multi-Agent Systems and Specialized Models (Self-paced)
LLM Architecture & Pre-training LLMs Specialized Session #4: Harnessing LLM Frameworks for Real-World Development (Self-paced)
Build Your Advanced Multi-Agent System
Live Guided Project: Call Center Conversational Audio Bot with GenAI Specialized Session #5: From Development to Deployment: Scaling and Debugging AI Models (Self-paced)
Evaluation & Optimizing AI Agents: Performance & Cost Efficiency Specialized Session 6: Managing Data Pipelines and Integrating APIs (Self-paced)
Designing Robust and Scalable AI Systems for Modern Applications
Capstone Project
Specialized Session 1: Laying the Groundwork for AI-Driven Development
3 sessions Bonus Content: Self-Paced
Python Fundamentals Refresher
Evolution of GenAI
Hands-on with Generative AI Models
ML Foundations

Live Guided Projects

Call Center Conversational Audio Bot with GenAI

Call Center Conversational Audio Bot with GenAI

  • Enhance call center operations with a voice-activated chatbot powered by Generative AI. Process audio inputs and generate context-aware responses for seamless customer engagement. Features include multilingual support, sentiment analysis, and conversation memory. Integrate Whisper, OpenAI GPT, and LangChain. Use FFmpeg for audio processing and build UIs with Streamlit and Gradio.

Healthcare Agent with LangGraph

Healthcare Agent with LangGraph

  • 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, RAG for medical knowledge retrieval, and Streamlit for the interface. Tools include Python, LangGraph, Pinecone, and OpenAI APIs.

Financial Multi-Agent System with LangGraph

Financial Multi-Agent System with LangGraph

  • 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.

Live Guided Projects

Call Center Conversational Audio Bot with GenAI

Call Center Conversational Audio Bot with GenAI

  • Enhance call center operations with a voice-activated chatbot powered by Generative AI. Process audio inputs and generate context-aware responses for seamless customer engagement. Features include multilingual support, sentiment analysis, and conversation memory. Integrate Whisper, OpenAI GPT, and LangChain. Use FFmpeg for audio processing and build UIs with Streamlit and Gradio.

Healthcare Agent with LangGraph

Healthcare Agent with LangGraph

  • 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, RAG for medical knowledge retrieval, and Streamlit for the interface. Tools include Python, LangGraph, Pinecone, and OpenAI APIs.

Financial Multi-Agent System with LangGraph

Financial Multi-Agent System with LangGraph

  • 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.

Capstone Projects

AI-Powered DevOps Assistant

AI-Powered DevOps Assistant

  • 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.

AI-Powered Patient Assistant

AI-Powered Patient Assistant

  • 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.

AI-Powered Security Auditor

AI-Powered Security Auditor

  • 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.

AI-Driven Legal Document Analyzer

AI-Driven Legal Document Analyzer

  • 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.

AI Supply Chain Optimization Assistant

AI Supply Chain Optimization Assistant

  • 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.

Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs

Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs

  • 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.

Call Center Summarization App Powered by LLMs

Call Center Summarization App Powered by LLMs

  • 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.

Email Generator App

Email Generator App

  • 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.

Resume/ATS scoring assistant

Resume/ATS scoring assistant

  • 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.

BYOP [Bring Your Own Project]

BYOP [Bring Your Own Project]

  • 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.

Capstone Projects

AI-Powered DevOps Assistant

AI-Powered DevOps Assistant

  • 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.

AI-Powered Patient Assistant

AI-Powered Patient Assistant

  • 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.

AI-Powered Security Auditor

AI-Powered Security Auditor

  • 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.

AI-Driven Legal Document Analyzer

AI-Driven Legal Document Analyzer

  • 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.

AI Supply Chain Optimization Assistant

AI Supply Chain Optimization Assistant

  • 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.

Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs

Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs

  • 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.

Call Center Summarization App Powered by LLMs

Call Center Summarization App Powered by LLMs

  • 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.

Email Generator App

Email Generator App

  • 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.

Resume/ATS scoring assistant

Resume/ATS scoring assistant

  • 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.

BYOP [Bring Your Own Project]

BYOP [Bring Your Own Project]

  • 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.

falag + Instructors to Train You

Get mentored by AI/ML leaders who are driving AI innovation at top global companies.

The IK Experience: What Our Alumni Are Saying

Our engineers land high-paying and rewarding offers from the biggest tech companies, including Facebook, Google, Microsoft, Apple, Amazon, Tesla, and Netflix.

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FAQs

No prior experience in AI or ML is required. If you have a solid software engineering background and are comfortable with Python or similar languages, you’ll be able to follow along. The course begins with foundational topics and gradually moves into advanced Agentic AI development.

 This is not a general-purpose ML or prompt engineering course. It is built specifically for software engineers who want to build deployable, production-ready agentic systems powered by LLMs, focused on real-world tools, architectures, and FAANG+ job expectations.

 You’ll build multiple hands-on projects, including a financial agent, a conversational audio bot, and your choice of one of 10+ capstones—like an AI-powered security auditor, DevOps assistant, or resume scoring tool. These are practical, portfolio-grade builds modeled after real AI workflows.

 Yes. Our BYOP (Bring Your Own Project) option lets you work on a personal or professional project with mentor feedback, ensuring it meets industry standards and strengthens your portfolio.

Agentic AI is already in use across multiple industries:

  • In development: to automate code review, CI/CD, and testing
  • In finance: for investment advice and risk analysis
  • In healthcare: for monitoring, diagnosis, and medical queries
  • In support: as autonomous chatbots and virtual agents
  • In logistics: for demand forecasting and operations

In robotics: for decision-making in dynamic environments

 Agentic AI refers to intelligent systems that can think through goals, decide how to achieve them, act, and learn autonomously. Unlike traditional AI that reacts to explicit instructions, agentic systems use LLMs and tools to operate proactively, adapt to feedback, and coordinate tasks without constant human input.

Capstone Projects are designed in consultation with FAANG+ mentors. They showcase your applied skills—something 67% of hiring managers prioritize over theory. Each project is reviewed for robustness, real-world relevance, and scalability—making your portfolio interview-ready.

You’ll attend live classes led by engineers from Google, Amazon, and other top companies. The program includes mock interviews, FAANG-specific prep, and project reviews—giving you exposure to the hiring bar of top-tier software engineering teams.

 You’ll work with over 30 tools used in modern AI engineering: LangChain, CrewAI, LlamaIndex, LangGraph, OpenAI APIs, Hugging Face, Streamlit, Docker, Kubernetes, and more. You’ll learn how to integrate and deploy them effectively.

 All instructors are experienced professionals from FAANG+ and Tier-1 companies. They’ve worked on production-grade AI systems and bring deep expertise in LLMs, agentic workflows, and GenAI tools.

 Plan to spend around 8 hours a week, including live classes, project work, and assignments. The full course includes 60+ hours of live teaching, 30+ hours of guided projects, and 21+ hours of specialized sessions over 14 weeks.

 It’s a hybrid model. You’ll attend weekly live sessions for core topics and projects, while the rest—including career prep and bonus modules—is self-paced for flexibility.

All live sessions are recorded and available on demand. You can catch up at your convenience and revisit sessions during project work or interviews.

 You’ll have access to 1:1 mentorship, dedicated TAs, technical coaches, and a peer learning community. Career support includes resume reviews, interview prep, and job targeting strategies.

Many of our alumni have transitioned into top-tier roles, with salaries averaging over 63LPA from top tier companies. We support your job hunt through tailored coaching, referrals, and portfolio development aligned with FAANG+ expectations.

 Yes. We offer flexible payment options and financing plans to make the course accessible for working professionals in India.

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Agentic AI Mastery For Experienced Engineers: Roadmap To Future-Proof Your Career

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