Master AI Agents, Build the Future! 150+ Hours of Comprehensive Learning 20+ Hands-on Projects for Skill Building 1:1 Mentorship with Agentic AI Experts Hours of Live Workshops Quarterly Hours of learning Become an Agentic AI Expert How does the Agentic AI Program help you? 150+ Hours of Intelligent Agent Training Build AI agents that think, learn, and act autonomously Master advanced Agentic AI frameworks and tools 50+ Real-World Projects Gain hands-on experience with practical simulations Tackle diverse projects to enhance your skills 1:1 Expert Mentorship Receive personalized guidance from industry leaders Accelerate learning with a tailored roadmap to success Curriculum Statistics Skill building with industry-relevant projects Comprehensive learning to power ahead in your AI journey Master 20+ cutting-edge tools and frameworks 15+ Assignments Work on Agentic AI assignments and test your skills 75+ Mentorship Sessions 1:1 mentorship session with leading AI experts Personalized Roadmap Chart your custom learning path, fueled by your ambition and built on your expertise 1 Introduction to Generative AI 2 Build Your First Agent 3 Learn Coding for Agentic AI 4 Learn LangChain, Prompt Engineering, RAG 5 Build an AI Agent from Scratch 6 Build ReAct Agents with LangChain 7 Build Your First AI Agent with LangGraph, Autogen, CrewAI 8 Learn Agentic AI Architectures & Design Pattern 9 Build Advanced AI Agents with LangGraph, Autogen, CrewAI 10 Build Agentic RAG Systems with LangGraph 11 Build Multi-agent Systems with LangGraph, Autogen, CrewAI 12 Build Reflective & Planning Agents with LangGraph, Autogen, CrewAI Go from beginner to expert in Agentic AI with 25+ courses Explore the Generative AI Universe Explore the Generative AI Universe Introduction to Generative AI Introduction to Generative AI Essentials of Prompt Engineering Essentials of Prompt Engineering Fine-Tuning RAGs and Agents Fine-Tuning RAGs and Agents From Prompt to Product: Vibe Coding with Windsurf From Prompt to Product: Vibe Coding with Windsurf Coding with Windsurf Coding with Windsurf Anyone can build AI Agents Anyone can build AI Agents Introduction to Agents Introduction to Agents Building Agents Building Agents Working with Complex Agents Working with Complex Agents Coding Essentials for Agents Coding Essentials for Agents Introduction to Python Introduction to Python Working with Files and Databases Working with Files and Databases Working with APIs Working with APIs Working with LLMs Working with LLMs Introduction to LangChain Introduction to LangChain Intro to the LangChain Ecosystem Intro to the LangChain Ecosystem LangChain Expression Language (LCEL) Essentials LangChain Expression Language (LCEL) Essentials Managing LLM Input / Output with LangChain Managing LLM Input / Output with LangChain Project: Prompt Engineering with LangChain and ChatGPT Project: Prompt Engineering with LangChain and ChatGPT Building LLM Chains and Conversational Applications with LangChain Building LLM Chains and Conversational Applications with LangChain Prompting Engineering Essentials Prompting Engineering Essentials Introduction to Prompt Engineering Introduction to Prompt Engineering Prompt Engineering Patterns Prompt Engineering Patterns Advanced Prompt Engineering Patterns Advanced Prompt Engineering Patterns Prompt Engineering with Open-Source LLM APIs Prompt Engineering with Open-Source LLM APIs Projects: Prompt Engineering with LLMs Projects: Prompt Engineering with LLMs RAG Systems Essentials RAG Systems Essentials Introduction to Rag system Introduction to Rag system Building Retrieval Systems - Loading Data Building Retrieval Systems - Loading Data Building Retrieval Systems - Splitting and Chunking Data Building Retrieval Systems - Splitting and Chunking Data Building Retrieval Systems - Vector Databases and Retrievers Building Retrieval Systems - Vector Databases and Retrievers Projects: Building Advanced RAG Systems Projects: Building Advanced RAG Systems Architecting Agentic AI: Design Patterns and Practices Architecting Agentic AI: Design Patterns and Practices Introduction to Agentic Design Patterns Introduction to Agentic Design Patterns The Reflection Pattern in Agentic AI The Reflection Pattern in Agentic AI The Tool Use Pattern in Agentic AI The Tool Use Pattern in Agentic AI The Planning Pattern in Agentic AI The Planning Pattern in Agentic AI The Multi Agent Pattern in Agentic AI The Multi Agent Pattern in Agentic AI Building AI Agents from Scratch Building AI Agents from Scratch Introduction to AI Agents Introduction to AI Agents Build a Reflection Agent from Scratch Build a Reflection Agent from Scratch Build a Tool-Using Agent from Scratch Build a Tool-Using Agent from Scratch Build a Planning Agent from Scratch Build a Planning Agent from Scratch Building a Multi-Agent System from Scratch Building a Multi-Agent System from Scratch Building AI Agents with LangChain Building AI Agents with LangChain Introduction to Tools and Tool Calling Introduction to Tools and Tool Calling Essentials of AI Agents with LangChain Essentials of AI Agents with LangChain Memory and Conversational Agents Memory and Conversational Agents Project: Build a Text2SQL AI Agent Project: Build a Text2SQL AI Agent Project: Build a Financial Analyst AI Agent Project: Build a Financial Analyst AI Agent Building your first AI Agent with LangGraph Building your first AI Agent with LangGraph Introduction to LangGraph Introduction to LangGraph Build AI Agents with LangGraph Build AI Agents with LangGraph Building your first AI Agent with CrewAI Building your first AI Agent with CrewAI Introduction to CrewAI Introduction to CrewAI Core Components of CrewAI Core Components of CrewAI What sets CrewAI apart? What sets CrewAI apart? Building Advanced AI Agents with LangGraph Building Advanced AI Agents with LangGraph Projects: Multi-User Conversational FInancial Analyst Tool-Use AI Agents with Memory Projects: Multi-User Conversational FInancial Analyst Tool-Use AI Agents with Memory Project: Build a Customer Support Router Agentic RAG System Project: Build a Customer Support Router Agentic RAG System Project: Build a Reflective Self-Correcting code Generation AI Agen Project: Build a Reflective Self-Correcting code Generation AI Agen Project: Build a supervisor Multi-Agent system for financial research and data analysis Project: Build a supervisor Multi-Agent system for financial research and data analysis Project: Build a Planning Agent for Deep Research & Structured Report Generation Project: Build a Planning Agent for Deep Research & Structured Report Generation Building Advanced AI Agents with AutoGen Building Advanced AI Agents with AutoGen Introduction to AutoGen Introduction to AutoGen Conversation Agents - Part 1 Conversation Agents - Part 1 Conversation Agents - Part 2 Conversation Agents - Part 2 Additional Applications with AG2 Additional Applications with AG2 Introduction to AutoGen Studio and Its Interface Introduction to AutoGen Studio and Its Interface Building Advanced AI Agents with CrewAI Building Advanced AI Agents with CrewAI Course Introduction and Recap Course Introduction and Recap Advanced Components of crewAI Advanced Components of crewAI Building Advanced Agents Building Advanced Agents Assembling Complex Crew Assembling Complex Crew Optimizating Agents Optimizating Agents Building Agentic RAG Systems with LangGraph Building Agentic RAG Systems with LangGraph Introduction to Agentic RAG and LangGraph Introduction to Agentic RAG and LangGraph Popular Agentic RAG Architectures Popular Agentic RAG Architectures Project: Build a Router RAG System Project: Build a Router RAG System Project: Build an Agentic Corrective RAG System Project: Build an Agentic Corrective RAG System Project: Build an Adaptive RAG System Project: Build an Adaptive RAG System Agent Operations Agent Operations Introduction to AI Agents and Multi-Agent Systems Introduction to AI Agents and Multi-Agent Systems Agent-Based Hotel Reservation System Agent-Based Hotel Reservation System Advanced AI Agent Orchestration Advanced AI Agent Orchestration Deploying and Scaling AI Agents Deploying and Scaling AI Agents Building a Social Media Agent using CrewAI Building a Social Media Agent using CrewAI Introduction to AI-Powered Social Media Automation Introduction to AI-Powered Social Media Automation Designing the AI Content Workflow Designing the AI Content Workflow Understanding CrewAI Understanding CrewAI Building Your Crew for Social Media Content Building Your Crew for Social Media Content Content Creation for Different Platforms Content Creation for Different Platforms Building AI-Powered Mock Interviewer with CrewAI Building AI-Powered Mock Interviewer with CrewAI Course Introduction Course Introduction Understanding the Agent System Architecture Understanding the Agent System Architecture Implementing our AI-Powered Mock Interviewer Implementing our AI-Powered Mock Interviewer Software Engineering Agents with LangGraph Software Engineering Agents with LangGraph Course Introduction Course Introduction Project Foundations Project Foundations Building Role-based Agents Building Role-based Agents Building Multi-Agent System Building Multi-Agent System Mini Projects & Wrap-Up Mini Projects & Wrap-Up Insights from Industry Leaders on AI Agents Global Leaders on the Future of Intelligent Autonomous Agents “We’ve seen that with the great technological revolutions of the past. Each technological revolution has gotten faster, and this will be the fastest by far. Helpful Agents Are Poised To Become AI’s Killer Function.” – Sam Altman, CEO of OpenAI “AI agents will become our digital assistants, helping us navigate the complexities of the modern world. They will make our lives easier and more efficient.” – Jeff Bezos, Founder and Executive Chairman of Amazon “AI agents will become the primary way we interact with computers in the future. They will be able to understand our needs and preferences, and proactively help us with tasks and decision making.” – Satya Nadella, CEO of Microsoft Tools you will master Gain expertise over critical libraries & frameworks Reinforce your learning with 50+ projects Projects prepare you for the fast moving industry and give you an edge over others to solve real world problems. Learning Objective: Build a basic AI agent from scratch Program it to research companies effectively Generate concise, informative company descriptions Build a Company Researcher Agent Learn to create a simple agent that researches a company and creates a short description Learning Objective: Develop an intelligent agent to review and refine resume content Customize the agent based on your chosen parameters Generate quality improvement suggestions to make your resume stand out Create a Resume Reviewer Agent Create a smart agent to edit and review your resume, offering tailored suggestions Learning Objective: Develop a chatbot designed to handle customer inquiries Implement functionality to analyze and understand customer problems Deliver accurate and relevant solutions based on the identified issues Build a Customer query Chatbot Build a chatbot to take care of customer queries and provide relevant resolutions based on their problems Learning Objective: Develop a sophisticated AI agent that compiles comprehensive product information Analyze customer data to identify the most suitable products for individual needs Generate tailored sales pitches to effectively engage potential customers Design a Sales Agent Build an advanced agent that consists of information regarding various products of the company Learning Objective: Discover the advanced capabilities of GPT-4o for processing multimodal data Analyze handwritten text, graphs, and charts for comprehensive insights Engage with diverse media formats, including images, audio, and video, to enhance understanding and application Multimodal Prompt Engineering with GPT-4o

Explores GPT-4o's multimodal capabilities, including handwritten text, graphs, charts, images, etc Learning Objective: Develop a foundational Retrieval-Augmented Generation (RAG) system Implement source citation for all generated responses Enhance information credibility by linking to original content Simple RAG System with Sources Building a basic Retrieval-Augmented Generation system that cites sources alongside the generated responses Learning Objective: Design a conversational RAG system that supports multiple users simultaneously Implement memory features to retain context across conversations Ensure the system provides accurate and relevant responses based on user interactions Multi-user Conversational RAG System Developing a conversational RAG system that can handle multiple users and conversations with memory to provide relevant responses Learning Objective: Integrate various data formats, including text, tables, and images, into a cohesive RAG pipeline Utilize multimodal language models (LLMs) to enhance data processing and analysis Enable the system to answer questions by leveraging diverse multimodal data sources effectively Multimodal RAG System Integrates multiple data formats (text, tables, images) into a RAG pipeline to leverage multimodal LLMs for answering questions Agentic Breakthrough Offer Use code AGENTICPRO and get flat 20% off the program fees. Become a certified Agentic AI professional today. Enrollment closes in AI-Powered Mentorship, On Demand Access a 24/7 AI mentor that delivers personalized learning paths, assessments, and continuous career guidance at scale. Meet the instructors & mentors Our instructor and mentors carry years of experience in data industry Chi Wang, Senior Staff Research Scientist at Google DeepMind, specializes in AI, machine learning, and data mining. Formerly a Principal Researcher at Microsoft Research, he holds a Ph.D. from UIUC and has driven advancements in web entity disambiguation, social network analysis, and AI-driven optimization. Senior Staff Research Scientist Miguel Otero Pedrido, a leader in AI and Machine Learning, is the Founder of The Neural Maze and a Senior Machine Learning Engineer at Dressipi. With 9 years of expertise in AI systems, MLOps, and AI agents, he has driven AI innovations at BBVA, Telefónica Tech, and Enagás. Miguel Otero Pedrido Eleni Verteouri, GenAI Tech Lead and Director - Conversational Banking at UBS, drives AI innovation and strategic partnerships. With 12 years of expertise in Generative AI, product management, and risk modeling, she has led AI transformations in finance. GenAI Tech Lead and Director - Conversational Banking Qingyun Wu, founder of AG2 (formerly AutoGen) and Assistant Professor at Penn State University, brings over seven years of expertise in AI and machine learning. Her work spans AI agents, reinforcement learning, and algorithm optimization, with roles at Microsoft, Adobe, and Yahoo driving advancements in AI technologies. Creator and Founder Alessandro Romano, Senior Data Scientist at Kuehne+Nagel, has over six years of experience in AI and data science. With roles at FREE NOW and Cargonexx GmbH, he specializes in building AI-driven solutions and AI agents to automate workflows and enhance efficiency. A skilled public speaker, Alessandro effectively bridges technical concepts with diverse audiences. Alessandro Romano Senior Data Scientist Pio Scelina is an experienced AI Agent developer with over 6 years of expertise in creating advanced AI solutions. His strong research background keeps him at the leading edge of new tools and applications, constantly driving innovation. Known for his passion for exploring emerging technologies and enhancing AI-driven experiences, Pio has established a reputation as a trailblazer in AI-powered transformation. AI Agent Developer Kamil Ruczynski is a seasoned AI Agent developer with over 7 years of experience in cutting-edge AI organisations. His deep expertise in research and development enables him to stay ahead of emerging trends and technologies, driving continuous innovation. Renowned for his dedication to pushing the boundaries of AI-driven applications, Kamil has earned recognition as a pioneer in creating transformative AI experiences Kamil Ruczynski AI Agent Developer Dipanjan has over 10+ years of hands-on and leadership industry experience as well as training, consulting and education initiatives in Data Science and Artificial Intelligence. Head of Community and Principal AI Scientist Bhaskarjit is an award-winning data scientist with a diverse background in multiple domains such as Retail, Airlines, Media & Entertainment, BFSI Bhaskarjit Sarmah Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- world's 2nd largest Data Science coummunity. Mani Kanteswara Rao Garlapati is an Associate Principal at Google, where he leads data science initiatives focused on fraud and spam detection across various Google products. With a strong background in machine learning and data science, he has previously held positions such as Lead Strategist at Google and Senior Data Scientist at Walmart Labs Associate Principal Lucas Soares is an AI Engineer at Otovo, focusing on AI-driven solutions through large language models (LLMs) and computer vision. With 6+ years of experience across sectors like biometrics and retail, he excels in developing machine learning tools Prashant Sahu, an IIT Bombay alumnus and seasoned Corporate Trainer in AI & ML, has over 17 years of diverse experience in areas like research, automation, and cryptography. His expertise extends to developing comprehensive Data Science training materials, including curriculum, case studies, and projects. Manager - Data Science - Instructor Apoorv Vishnoi, a seasoned professional with over 13 years of experience, including more than 10 years in Machine Learning and AI. He holds an MBA from the prestigious Indian School of Business and several certifications in Data Science and Deep Learning. His ability to simplify complex concepts in Data Science and Machine Learning has established him as a respected and influential instructor. Head - Training Initiative Instructor-Led Live Workshops Live Agentic AI workshops : Solve real-world problems with expert insights Learning Objective: Manage multi-turn conversations effectively. Apply advanced prompting techniques for complex tasks. Design chatbot scenarios and analytical reports. Understand AI limitations and ethical considerations. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering Prompt Engineering II Learning Objective: Learn memory management and snapshots for AI Agents. Build conversational Agents with persistent memory. Develop a financial analyst Agentic system. Create adaptive Agents that retain context and improve over time. Upcoming 7:00 PM - 10:00 PM (IST) IST Building Advanced AI Agents with LangGraph - I (Conversational Agents) Learning Objective: Understand the importance of prompt engineering. Learn to craft clear, specific, and contextual prompts. Apply few-shot prompting techniques for better AI responses. Refine generated content through iterative improvements. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering Prompt Engineering I Learning Objective: Learn LangChain fundamentals for building AI Agents. Explore prompts, chat models, tools, and function calling. Develop tool-use Agents with hands-on exercises. Integrate memory to create adaptive conversational Agents. Upcoming 7:00 PM - 10:00 PM (IST) IST Building AI Agents with LangChain Learning Objective: Differentiate RAG from prompt engineering and fine-tuning. Learn when to use RAG versus other approaches. Understand Retrieval-Augmented Fine-Tuning (RAFT). Build, tune, and evaluate a RAG pipeline. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering RAG Systems I Learning Objective: Compare GraphRAG with traditional RAG systems. Build and store knowledge graphs in graph databases. Create and evaluate GraphRAG pipelines. Understand the architecture and key components of a RAG system. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering RAG Systems II AV Assisted Placements Our alumni excel at top firms-highlights from 1200+ success stories Assistant Manager - Analytics Ashiwn Deendayalan Assistant Manager - Analytics Assistant Manager - Analytics Industry-Recognized Certification Get certied in Agentic AI from Analytics Vidhya and Western State University, and share your achievement with the world AV Learners Spotlight All my expectations from the course and workshops have been fulfilled I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons. Sr. Level Strategic Planning Executive I found future learning with Gen AI very interesting I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons. Arunima R Pillai ML Engineering Analyst The program has all the cutting edge technologies covered I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons. Staff Data Scientist I really value the personalised mentorship sessions which came with the program I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons. Mentors of Analytics Vidhya have business experience and are practitioners themselves I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons. Application Developer The content Analytics Vidhya provided was far better than any other organisation I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons. Parikshit Rathode Senior AI & ML Developer Money Back Guarantee! Agentic AI Pioneer program comes with 7 days no questions asked Money back Guarantee. If the program is bought in pre-launch offer or on discounted price, then the fee paid is non-refundable. For more T&C, Click here Invest in your future today Build expertise with cutting-edge Agentic AI frameworks Boost Your Career Fast-track your growth with personalized mentorship. Enroll now and start your journey to becoming an Agentic AI expert. Customized Roadmap for Career Success 20+ Cutting edge tools and frameworks 50+ Projects for Experiential Learning Enroll now and become an Agentic AI expert Secure your spot and begin the journey to exceptional growth Contact Us Today Take the first step towards a future of innovation & excellence with Analytics Vidhya Upskill, Reskill, Thrive Get Expert Guidance Need support? We've got your back anytime! +91-9354711240 10AM - 7PM (IST) Mon-Sun [email protected] You'll hear back in 24 hours [email protected] Frequently asked questions Looking for answers to other questions? What Are Agents in AI? AI agents are autonomous systems designed to sense their environment, process information, and perform actions to achieve specific goals. They function by leveraging AI techniques like machine learning, natural language processing, and decision-making algorithms to automate or assist with tasks. You’ll learn about the role of agents in the AI ecosystem and their real-world applications in the Introduction to Generative AI module. What Are the 5 Types of AI Agents? AI agents are classified into five types based on their complexity and interaction with the environment: Simple Reflex Agents: Follow predefined rules to respond to stimuli. Model-Based Reflex Agents: Use internal models to predict outcomes. Goal-Based Agents: Make decisions aimed at achieving specific objectives. Utility-Based Agents: Evaluate and optimize outcomes for maximum utility. Learning Agents: Improve their performance through experience. These types are discussed in detail in the Agents and Their Applications module. Is ChatGPT an AI Agent? Yes, ChatGPT is an AI agent specializing in conversational tasks. It uses advanced natural language processing capabilities to understand queries and provide human-like responses, making it a versatile tool for automating communication. The Exploring LLMs module explains how conversational agents like ChatGPT utilize large language models effectively. We empower the next wave of AI professionals We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy & Cookies Policy . This site uses cookies to ensure that you get the best experience possible. 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