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

Python For GenAI

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

AI SDE-Specific Career Guidance & 1:1 Mentoring

3 sessions Bonus Content: Self-Paced

Foundational Materials

Python Fundamentals Refresher

Evolution of GenAI

Hands-on with Generative AI Models

ML Foundations

Live Guided Projects

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

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

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.

Capstone Projects

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

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

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

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

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

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

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

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

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]

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.

+ Instructors to Train You

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

Mona Mona

Generative AI Lead

Ralph Blanes

Research Software Engineer

Rishabh Misra

Lead ML Engineer & Researcher

Behnoosh Parsa

Applied Scientist - GenAI

Ujjwal Das Gupta

Senior ML Engineer

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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.

Venkatesh Babu

Senior Director - ISV/SolEx Technical Partner Management

I highly recommend the Applied GenAI course by Interview Kickstart. The PM path was incredibly well-organized, reshaping my thinking on how to leverage Generative AI in product management. The hands-on approach, insightful curriculum, and experienced instructors made it an outstanding learning experience!

Amit Vaswani

Lead Software Engineer, Highnote

I recently completed the Applied Gen AI course at Interview Kickstart, and I couldn't be more impressed. The course was well-structured into modules, making complex concepts easier to digest. For someone without a strong programming background, I appreciated the beginner Python class they offer for non-programmers—it helped build a solid foundation. The instructors are fantastic and always go the extra mile to ensure every question is answered. They are patient and don’t rush through the material, often allowing classes to run over to ensure everyone fully grasps the concepts. One of my favorite features is the 'Expert Connect,' where you can have 1-on-1 sessions with instructors to clear any doubts. Overall, Interview Kickstart provided an exceptional learning experience, and I highly recommend it to anyone looking to uplevel in their career.

Abhishek Singh

Senior Data Analyst, Jeavio

IK is a GOD-Send to me. If you are looking to upskill or transition in your career, IK is the place to be. I joined Data Science Switchup in November-23 and I am loving the 360 degree experience which IK provides. The instructors are professionals who are currently working in the tier-1 companies so the classes have loads of real-life snippets of their experience which adds true value to students like us. The mock sessions and technical sessions helped me immensely to understand the topic at a deeper level. The Ops Team & Success Coaches are superstars who act like a true friend when you need any sort of assistance.

Dwaraknath Bakshi

Senior Director of Engineering, Freshworks

IK has been an integral part of my life for last seven years. Since being part of some of the early batches to most recently pursuing their ML track I have done several courses with them. What amazes me is the approachability of the staff, the proactive support team and professionalism. The material is amazing and profound. Omkar and Niloy to name a few they have amazing faculty who are very knowledgeable and are also great teachers. I can keep raving about IK. It’s definitely a boon to software engineers.

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FAQs

Do I need prior AI or ML experience to join this course?

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.

How is this different from a standard ML or AI bootcamp?

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.

What kinds of projects will I build in this course?

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.

Can I bring my own project to the course?

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.

What are the practical applications of Agentic AI?

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

What is Agentic AI, and how is it different from traditional AI?

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.

How do the Capstone Projects help my job prospects?

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.

How does this course support my transition into FAANG+ roles?

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.

What tools and frameworks will I gain experience with?

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.

Who teaches the program?

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.

What’s the weekly time commitment for this course?

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.

Is this course live, self-paced, or both?

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.

What if I miss a live session?

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

What kind of support will I receive during the course?

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.

What career outcomes can I expect after completing this course?

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.

Are there financing or payment plans available?

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