Go beyond chatbots. Learn to design, build and deploy AI agents that plan, use tools, and complete complex multi-step tasks autonomously.
Traditional AI responds to prompts. Agentic AI breaks down goals, plans actions, uses tools, executes tasks, and loops until the job is done — autonomously.
Agents perceive context, break goals into sub-tasks, and plan sequences of actions using LLM reasoning and chain-of-thought techniques.
Agents use tools — web search, code execution, APIs, databases — and maintain short & long-term memory across complex, multi-step tasks.
Multiple specialised agents work in parallel — a researcher, a coder, a writer — orchestrated by a master agent to complete complex workflows.
Agents evaluate their own outputs, detect errors, and self-correct — leading to significantly better results than single-pass AI responses.
Autonomously searches the web, reads papers, synthesises findings, and writes comprehensive research reports with citations.
Reviews pull requests, identifies bugs, suggests fixes, runs tests, and even implements approved changes autonomously in CI/CD pipelines.
Connects to databases, runs SQL queries, generates Python visualisations, interprets results, and creates executive summaries automatically.
Reads emails, drafts replies, schedules meetings, manages conflicts, and handles routine correspondence — saving hours of administrative work.
Monitors inventory, updates product listings, responds to customer queries, processes returns, and generates daily business reports.
Collects patient symptoms, matches against medical knowledge bases, prioritises cases, schedules appointments, and alerts doctors for critical cases.
The most widely used agentic AI framework. Build chains, agents, tools and RAG pipelines in Python or JavaScript.
Build teams of AI agents with defined roles, goals, and backstories. Great for complex multi-agent workflows.
Microsoft's framework for multi-agent conversations. Supports human-in-the-loop and autonomous agent collaboration.
Graph-based orchestration for complex multi-step agentic workflows with cycles, branching, and parallel execution.
Anthropic's native agentic capability — Claude can use computers, browse web, write and run code autonomously.
GPT-4o assistants with persistent threads, file retrieval, code interpreter, and function calling built in.
Production-ready NLP framework with agent capabilities. Best for retrieval-augmented generation pipelines.
Visual workflow automation with AI nodes. Perfect for non-developers to build agentic workflows without code.
Learn Python basics, REST APIs, JSON handling, and async programming. These are the building blocks for every agentic AI project.
Understand how LLMs work, chain-of-thought reasoning, few-shot prompting, and using Claude/GPT APIs effectively.
Give AI agents the ability to call external tools — web search, calculators, APIs, databases. This is the core of agentic behaviour.
Build retrieval-augmented generation pipelines. Give agents persistent memory using vector databases like Pinecone and Chroma.
Build a complete agentic system — a research agent that searches the web, extracts data, and writes reports using LangChain or CrewAI.
Design and orchestrate networks of specialised agents. Learn about agent communication, delegation, and conflict resolution.
Deploy agentic AI systems at scale — monitoring, safety guardrails, human-in-the-loop checkpoints, and cost optimisation strategies.
A full-day hands-on workshop — build your first autonomous AI agent in Python from scratch. Limited seats available. Location: 91springboard, Jaipur.