Unleash the Power of AI Agents to Supercharge Your Career Growth

Go beyond traditional AI—master Agentic AI to build, optimize, and deploy intelligent AI workflows to drive efficiency and innovation

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Course Highlights

Suitable for

Tech professionals from any domain who want to build AI Agents and lead AI-driven automation strategies with FAANG+ mentorship

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

Projects

2 Live Guided Projects, Multiple Capstone Projects to choose from

Customised Learning Tracks

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

Instructors

Generative & Agentic AI Practitioners from FAANG and other Tier 1 companies of the world

Curriculum coverage

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

EdgeUp

Additional FAANG+ interview preparation for the AI-enhanced roles you’d apply for

Average package for alumni

$ 112275

Careers transformed

0 K+

Average ROI on course price

0 x

50+ Tools & Tech You’ll Learn

Why Choose Interview Kickstart’s Agentic AI Program

Navigate the AI Buzz:

Cut through the AI noise and master the key AI automation skills that employers demand, to position yourself at the forefront of Agentic AI.

Industry-Aligned Curriculum

Learn the full spectrum of Agentic AI, from foundations to real-world deployment, gaining expertise in AI agent workflows and automation.

Hands-on Experience Through Projects

Gain hands-on training in building AI agents to solve complex industry challenges, such as fraud detection and security threat mitigation.

Domain-Specific Learning

Focus on tailored AI applications and leverage the power of Agents relevant to PMs, TPMs, EMs, and SDEs. Topics include AI-powered product execution, LLMOps, technical feasibility, and managing AI teams.

Proven Learner Satisfaction:

With an NPS Score of 55 & and average rating of 4.75+ for our Applied GenAI program, learners love our structured and hands-on approach.

Endorsed by Over 700 FAANG+ Mentors

Learn cutting-edge Agentic AI live with FAANG+ experts who bring practical, cutting-edge insights to the class

Register Now!

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Detailed Curriculum of Our Agentic AI Program

Applied Agentic AI for Tech Professionals

Fundamentals of Agentic AI

Build Your First AI Agent

Building Applications with LLMs & Agents - Lite

Build Your Advanced Agent

Evaluation & Optimizing AI Agents: Performance & Cost Efficiency

Python Fundamentals Crash Course

Python For GenAI

LLM Architecture & Pre-training (Deep Dive into LLMs + Training LLMs) - Lite

Live Guided Project - Automated Data Insights Generator

Capstone Projects

Applied Agentic AI for SWEs

Python For GenAI

Fundamentals of Agentic AI

Build Your First AI Agent

Building Applications with LLMs & Agents - Lite

Building Applications with LLMs & Agents - Advanced

Evaluation & Optimizing AI Agents: Performance & Cost Efficiency

LLM Architecture & Pre-training (Deep Dive into LLMs + Training LLMs)

Build Your Advanced Agent

Live Guided Project 1: Conversational Audio Bot Project

Evaluation & Optimizing AI Agents: Performance & Cost Efficiency

Designing Robust and Scalable AI Systems for Modern Applications

Capstone Project

Bonus Content: Self-Paced

Foundational Materials

Python Fundamentals Refresher
Python for GenAI
Evolution of GenAI
ML Foundations

Specialized Sessions

Laying the Groundwork for AI-Driven Development
Building Effective Prompts and Configuration-Driven Apps

Innovating with Multi-Agent Systems and Specialized Models
Harnessing LLM Frameworks for Real-World Development
From Development to Deployment: Scaling and Debugging AI Models
Managing Data Pipelines and Integrating APIs

Hands-on with Generative AI Models (Live assignment review)

Applied Agentic AI for PMs

Fundamentals of Agentic AI

Build Your First AI Agent

Building Applications with LLMs & Agents - Lite

Build Your Advanced Agent

Evaluation & Optimizing AI Agents: Performance & Cost Efficiency

Python Fundamentals Crash Course

Python For GenAI

LLM Architecture & Pre-training (Deep Dive into LLMs + Training LLMs) - Lite

Live Guided Project - Automated Data Insights Generator

Capstone Project 1: Conceptualize the integration of GenAI into an existing Product

Domain-specific case studies I

Capstone Project 1: Final Presentation, Peer Review & Live Feedback Capstone Project 2 Initiation: Build a Low-Code/No-Code AI Agent to optimize a workflow for your domain

Domain-specific case studies II

Capstone Project 2: Final Presentation, Peer Review & Live Feedback

Specialized Sessions

Applied Agentic AI for TPMs

Fundamentals of Agentic AI

Build Your First AI Agent

Building Applications with LLMs & Agents - Lite

Build Your Advanced Agent

Evaluation & Optimizing AI Agents: Performance & Cost Efficiency

Python Fundamentals Crash Course

Python For GenAI

LLM Architecture & Pre-training (Deep Dive into LLMs + Training LLMs) - Lite

Live Guided Project - Automated Data Insights Generator

Capstone Project 1: Create a stakeholder management plan for an AI/ML program, analyzing stakeholders’ interests and engagement strategies

Domain-specific case studies I

Capstone Project 1: Final Presentation, Peer Review & Live Feedback Capstone Project 2 Initiation: Build a Low-Code/No-Code AI Agent to optimize a workflow for your domain

Domain-specific case studies II

Capstone Project 2: Final Presentation, Peer Review & Live Feedback

Specialized Sessions

Applied Agentic AI for EMs

Fundamentals of Agentic AI

Build Your First AI Agent

Building Applications with LLMs & Agents - Lite

Build Your Advanced Agent

Evaluation & Optimizing AI Agents: Performance & Cost Efficiency

Python Fundamentals Crash Course

Python For GenAI

LLM Architecture & Pre-training (Deep Dive into LLMs + Training LLMs) - Lite

Live Guided Project - Automated Data Insights Generator

Capstone Project 1: Strategic planning & Change Management for GenAI Project from Leadership perspective - Build vs Buy, System Design, Ethical Considerations, etc.

Domain-specific case studies I

Capstone Project 1: Final Presentation, Peer Review & Live Feedback Capstone Project 2 Initiation: Build a Low-Code/No-Code AI Agent to optimize a workflow for your domain

Domain-specific case studies II

Capstone Project 2: Final Presentation, Peer Review & Live Feedback

Specialized Sessions

Detailed Curriculum of Our Agentic AI Program

Live Guided Projects and Capstone Projects

Software Engineers

Choose from one of 10 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 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

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.

Product Managers

AI-Powered Feature Prioritization Tool

Design a tool meant to evaluate feature requests based on user impact, development effort, and business alignment. It leverages AI to analyze customer feedback and trends using LLMs, ensuring data-driven decision-making. The tool integrates with Jira and Asana to automatically generate tickets for prioritized features, streamlining the product development workflow and improving efficiency.

Customer Sentiment Analysis & Roadmap Alignment Tool

Build a tool that leverages AI to analyze customer complaints, app reviews, and support tickets. It should be able to classify and cluster feedback into product themes, providing insights into common pain points. The system automatically generates reports that align key customer concerns with upcoming roadmap items, ensuring that product development stays focused on user needs and priorities.

AI-Driven Competitive Landscape Analysis Tool

Build an AI-powered research assistant that monitors competitor websites, product releases, and industry news. Using retrieval-augmented generation (RAG), it will generate reports summarizing key competitive insights, including pricing strategies, feature gaps, and market trends. This enables businesses to stay ahead by making informed strategic decisions based on real-time industry analysis.

PM and TPM capstone projects

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.

Technical Program Managers

AI-Powered Stakeholder Management Bot

Build a system that will help TPMs track and manage stakeholder interactions by summarizing emails, meeting transcripts, and sentiment trends. It alerts TPMs when key stakeholder engagement scores decline, enabling proactive relationship management.

Multi-Agent AI System for Program Risk Management

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.

AI-Driven Engineering Capacity & Resource Allocation Agent

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.

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.

Engineering Managers

Multi-Agent System for Engineering Productivity & Burnout Monitoring

Build a system that tracks engineering efficiency and detects burnout risks. It includes a workload analysis agent monitoring sprint progress, a burnout detection agent analyzing work hours and meeting fatigue, and an optimization agent suggesting workload balancing. Integrated with Jira and Slack, this CrewAI-based system will enhance team well-being and productivity.

Multi-Agent AI System for Engineering Roadmap & Strategy Planning

Automate strategic planning by designing a system that analyzes industry trends, workload, and tech stack evolution. It features agents for tracking technology trends, evaluating new frameworks, and adjusting roadmaps based on resources. Use LangGraph, OpenAI, and real-time web scraping to ensure data-driven decision-making.

AI Agent for Cloud Cost Optimization in Engineering Workloads

Automate cost tracking and optimization for AI/ML workloads with a multi-agent system that monitor cloud spend across AWS, GCP, and Azure, suggest cost-effective configurations, and alert teams to unexpected spikes. Leverage LangChain, AWS Cost Explorer API, and Terraform, to optimize cloud expenses efficiently.

Tech Professionals

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 Project Management & Task Automation

Build a system that leverages multi-agent technology to streamline project workflows. The system will employ specialized agents for task prioritization, resource allocation, and progress monitoring, with each agent handling specific aspects like urgency assessment, manpower distribution, and KPI tracking. Use tools like LangGraph, Jira API, OpenAI, and Zapier to create comprehensive project automation capabilities.

AI-Powered Knowledge Management & Retrieval System

Build a specialized assistant designed to help professionals access information efficiently. Using a multi-agent approach, combine a document ingestion agent for scanning various formats, a semantic search agent for precise information retrieval, and a summarization agent that delivers concise explanations. The system will be built on RAG architecture, utilizing OpenAI and vector databases like Pinecone/Weaviate for optimal performance.

Projects are subject to change as per industry inputs.

Live Guided Projects and Capstone Projects

Software Engineers

Choose from one of 10 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 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

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.

Product Managers

AI-Powered Feature Prioritization Tool

Design a tool meant to evaluate feature requests based on user impact, development effort, and business alignment. It leverages AI to analyze customer feedback and trends using LLMs, ensuring data-driven decision-making. The tool integrates with Jira and Asana to automatically generate tickets for prioritized features, streamlining the product development workflow and improving efficiency.

Customer Sentiment Analysis & Roadmap Alignment Tool

Build a tool that leverages AI to analyze customer complaints, app reviews, and support tickets. It should be able to classify and cluster feedback into product themes, providing insights into common pain points. The system automatically generates reports that align key customer concerns with upcoming roadmap items, ensuring that product development stays focused on user needs and priorities.

AI-Driven Competitive Landscape Analysis Tool

Build an AI-powered research assistant that monitors competitor websites, product releases, and industry news. Using retrieval-augmented generation (RAG), it will generate reports summarizing key competitive insights, including pricing strategies, feature gaps, and market trends. This enables businesses to stay ahead by making informed strategic decisions based on real-time industry analysis.

PM and TPM capstone projects

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.

Technical Program Managers

AI-Powered Stakeholder Management Bot

Build a system that will help TPMs track and manage stakeholder interactions by summarizing emails, meeting transcripts, and sentiment trends. It alerts TPMs when key stakeholder engagement scores decline, enabling proactive relationship management.

Multi-Agent AI System for Program Risk Management

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.

AI-Driven Engineering Capacity & Resource Allocation Agent

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.

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.

Engineering Managers

Multi-Agent System for Engineering Productivity & Burnout Monitoring

Build a system that tracks engineering efficiency and detects burnout risks. It includes a workload analysis agent monitoring sprint progress, a burnout detection agent analyzing work hours and meeting fatigue, and an optimization agent suggesting workload balancing. Integrated with Jira and Slack, this CrewAI-based system will enhance team well-being and productivity.

Multi-Agent AI System for Engineering Roadmap & Strategy Planning

Automate strategic planning by designing a system that analyzes industry trends, workload, and tech stack evolution. It features agents for tracking technology trends, evaluating new frameworks, and adjusting roadmaps based on resources. Use LangGraph, OpenAI, and real-time web scraping to ensure data-driven decision-making.

AI Agent for Cloud Cost Optimization in Engineering Workloads

Automate cost tracking and optimization for AI/ML workloads with a multi-agent system that monitor cloud spend across AWS, GCP, and Azure, suggest cost-effective configurations, and alert teams to unexpected spikes. Leverage LangChain, AWS Cost Explorer API, and Terraform, to optimize cloud expenses efficiently.

Tech Professionals

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 Project Management & Task Automation

Build a system that leverages multi-agent technology to streamline project workflows. The system will employ specialized agents for task prioritization, resource allocation, and progress monitoring, with each agent handling specific aspects like urgency assessment, manpower distribution, and KPI tracking. Use tools like LangGraph, Jira API, OpenAI, and Zapier to create comprehensive project automation capabilities.

AI-Powered Knowledge Management & Retrieval System

Build a specialized assistant designed to help professionals access information efficiently. Using a multi-agent approach, combine a document ingestion agent for scanning various formats, a semantic search agent for precise information retrieval, and a summarization agent that delivers concise explanations. The system will be built on RAG architecture, utilizing OpenAI and vector databases like Pinecone/Weaviate for optimal performance.

Projects are subject to change as per industry inputs.

+ Instructors to Train You

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

Mona Mona

Generative AI Lead

Jigyasa Grover

AI & Research Lead,

Ralph Blanes

Research Software Engineer

Rishabh Misra

Lead ML Engineer & Researcher

Behnoosh Parsa

Applied Scientist - GenAI

Ujjwal Das Gupta

Senior ML Engineer

Register Now!

And learn all you need to know about the course

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.

Register Now!

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FAQs

What is the difference between Traditional AI and Agentic AI?

Traditional AI models focus on single-task execution, while Agentic AI enables AI agents to reason, plan, and collaborate autonomously. This course teaches multi-agent orchestration, decision-making AI, and AI automation.

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

No, but basic programming knowledge is recommended. The course is designed for technical professionals looking to implement AI-driven automation.

What are the prerequisites for this course?

Basic Python knowledge (preferred but not mandatory)
Interest in AI automation, intelligent workflows, and AI-driven decision-making
Willingness to learn programing/Vibe coding

How does this course differ from the other AI/ML courses?

Unlike most courses focusing only on prompt engineering and LLMs, this program provides:

Hands-on training with AI agents (CrewAI, LangChain, AutoGen, etc.)
Multi-agent orchestration for real-world AI workflows
Practical deployment strategies using cloud & AI automation frameworks.

What kind of projects will I work on?

You’ll build real-world AI automation systems, such as:

Agentic RAG for Finance & e-commerce
Cybersecurity Threat Investigation Agents
AI Workflow Automation for Business Operations

Will I receive a certificate upon completion?

Yes, all learners receive a certificate of completion.

What kind of technical support is available?

The program includes:

1:1 doubt resolution from AI industry experts
Project reviews & networking with AI professionals
Guidance for transitioning into AI roles

Why should I buy this course? How will this course help my specific domain?

Software Engineers & AI Engineers get to

Learn Agentic AI Engineering – build, optimize & deploy AI-driven backend systems.
Hands-on with LangChain, CrewAI, AutoGen & productionizing AI workflows.
Master AI orchestration, automation & real-time inference in modern applications.

Product Managers & AI PMs will be able to:

Build Agentic AI strategies to drive product innovation & prototyping.
Learn to integrate AI-first automation into real-world workflows.
Hands-on experience with multi-agent AI architectures for AI-powered products.

Technical Program Managers (TPMs) will:

Gain expertise in AI system design & AI-first execution roadmaps.
Learn to orchestrate multi-agent workflows for large-scale AI deployments.
Bridge the gap between AI engineering, strategy & execution in AI-driven programs.

Engineering Managers & Tech Leaders get to:

Learn AI-driven automation strategies to optimize engineering workflows.
Manage multi-agent AI teams and drive AI-led transformation.
Design, scale & deploy Agentic AI systems for enterprise applications.

Other tech professionals in the domains of Cloud, DevOps, Security, Data, and Machine Learning will be able to:

Learn AI implementation & system integration for production environments.
Use AI agents to automate cloud, security & DevOps workflows.
Deploy AI models efficiently with LLMOps, RAG, & scalable AI pipelines.