Certification Workshop – Building Agents with LangChain and LangGraph

Building Agents with LangChain and LangGraph is your gateway to mastering real-world AI agent development. This hands-on certification workshop empowers learners to build robust multi-agent systems using LangChain and LangGraph. Immerse yourself in practical applications of agentic search, structured knowledge retrieval and industry standard orchestration frameworks; all in one comprehensive training. The Certification Workshop on LangChain and LangGraph breaks down the complexities of LLM responsibilities, system flow and persistent session management to equip you for cutting-edge AI engineering roles.

Add to Cart

₹2,999.00

(Limited seats)

Who Should attend this workshop?

Entrepreneurs

Software Engineers

Mid-level Managers & PMs

AI / Deep Learning Students

Al enthusiasts/ Researchers

What You Will Learn

In this hands-on workshop, you will learn how to build your own AI-powered Startup Advisor using open-source tools. Step by step, you’ll discover how to:

Use LangChain to build simple AI agents
Break down a task into smaller parts for different agents to handle
Search the web using AI and get clear, useful answers(not just links)
Organize agents into a flexible system using LangGraph
Save your agent’s state so you can pick up where you left off
Add human input to guide and improve your AI's responses

By the end, you will walk away with a working multi-agent system you can use and build on, opening up new business and career opportunities for you in the rapidly evolving AI landscape.

Date: Saturday, August 30 2025, 10:00 AM – 3:00 PM

Mode: Offline & Online

Venue: IKP Eden, Koramangala, Bengaluru

Seats Are Filling Fast!

Don’t miss your chance to learn one of the most in-demand AI frameworks of 2025, straight from industry experts.

Offers:

EARLY BIRD Offer: Instant discount of ₹ 1,000 for first 10 registrations (Final Price: ₹ 1,999) by using coupon code EARLY1000
TEAM UP Offer: Register with two or more colleagues from your organization and receive a 33% discount on all seats by using coupon code COLABAI33.

Please note that we will not be able to accommodate walk-ins at this event. Prior registration is required to reserve your seat. Please bring your own laptop.

Please reach Nihal at 9663374431 if you need any clarifications or have any challenges in registration.

Days

Hours

Minutes

Seconds

AGENDA

10:00 AM – Introduction & Agenda Overview

Overview of multi-agent systems and real-world use cases
Introduction to LangChain and LangGraph
Workshop objectives and output expectations

10:15 AM – Environment Setup

Setting up the coding platform
Installing dependencies (langchain, langgraph, openrouter, serpapi, etc.)
Securing API keys using .env files

10:30 AM – Part 1: Building an Agent from Scratch

Define use case and identify subtasks
Build prompts and simple function wrappers
Discussion: Division of labor between LLM and code logic

11:30 AM – Implementing Agentic Search

Use SerpAPI or DuckDuckGo search tool
Structure output in a predictable format
Emphasize structured data retrieval vs traditional web search

12:00 Noon – Break

1 hour lunch break

01:00 PM – Part 2: Rebuilding the System with LangGraph

Brief overview of LangGraph (nodes, edges, states) - Define graph flow: start → idea → research → gtm → end
Add optional conditional path
Visualize and execute graph

01:45 PM – Persistence and Session Management

Use a simple in-memory or JSON store to retain state
Implement load/save conversation features
Session switching, continuation, and threading

2:15 PM – Human-in-the-Loop Integration

Adding manual approval steps
Basic CLI prompts or Colab widgets for interaction
Integration points for feedback loops

2:30 PM – Final Testing and Demonstration

Run the end-to-end Startup Advisor Bot
Try diverse domains (e.g., climate, SaaS, retail)
Highlight how modular agents communicate and share state

3:00 PM – Wrap-Up and Next Steps

Summary of key concepts and capabilities
Share complete project code, diagrams, and documentation
Discuss advanced extensions: UI deployment, multi-user systems, evaluation methods

3:15 PM – Networking Over Tea and Certificate Distribution

Wrap up with refreshments, connect with peers and mentors and receive your certificate of participation.

Post-Workshop Resources Provided

01

Notebook / Python script with full code

02

Agent architecture diagram (LangChain & LangGraph)

03

API key configuration instructions

04

Starter templates for future agentic workflows

05

Example outputs for testing (sample startup ideas and responses)

06

Become a part of a community of like minded AI enthusiasts

New to AI Agents?

Organizers

SunitechAI

SunitechAI aims to provide professional training and educational courses in Data Science and Artificial Intelligence (AI) technologies, equipping individuals and organizations with advanced skills in these high-demand fields. Additionally, it offers corporate consulting services to help businesses leverage Data Science and AI for enhanced decision-making.

Deep Tech Stars

This is one of the largest global meetup communities of AI developers. We have conducted AI-focussed meetups, workshops, course, hackathons, project sessions and more every month for the last 10 years.

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leadership accelerator, high-performance leadership — Computer Vision and Natural Language Processing Bootcamp
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About Faculty

Shubham has 9+ years of experience in Data Science and is currently building SunitechAI, which is an AI-powered upskilling platform. He offers consulting to companies on a variety of Data Science problems and has developed internal tools for Anomaly Detection & Classification in AWS for Quickbase, Boston, USA. He mentors and advises working professionals on the latest data science tools and technologies, moderates live sessions from MIT Professors (Cambridge, MA, USA) and provides advice on business problems as a Guest Mentor. He has done Masters in Data Science from SUNY Buffalo, New York, USA, holds a B.Tech in Petroleum Engineering from IIT(ISM) Dhanbad and has worked in the Data Science team at Baker Hughes (a global oil and gas service company).

Benefits

Exclusive invite to Sagemind, the AI-Powered LMS from SunitechAI

Flat 10% off coupon code applicable on all SunitechAI’s courses

Early access to SunitechAI’s upcoming workshops & events

Priority access to the upcoming workshops by Deep Tech Stars

Testimonials

Amazing Learning Experience

Shubham is one of the best Instructors I have known. He is very polite, humble, handles annoying questions with great patience, while understanding the audiences' question.

Vamsi Kethu

Great Experience

The debrief was particularly worthwhile. There were some things that I'd forgotten to consider in my project. Will carry the techniques forward for the next one!”

Gregory Benet Timmons

Best teacher so far!

The lessons are engaging, easy to understand, and truly inspiring. Their teaching style makes complex topics simple, ensuring every student feels confident. Highly recommend for anyone looking to learn effectively!"

Dr. Parag A Deshmukh

FAQs

What are the prerequisites for optimal course comprehension?

Learners should have basic proficiency in a programming language (e.g. Python) and basic understanding of LLMs and GenAI concepts is recommended for optimal learning. If you are new to Large Language Models, our LLMs: Applications in Enterprises course is ideal. It focuses on the core understanding of the Transformer architecture and foundational models.

What is LangGraph?

LangGraph is a cutting-edge open-source framework that makes building, deploying and managing AI agents simple. This framework visualizes workflows as graphs using directed acyclic graphs (DAGs). You will find this approach intuitive if you are familiar with data processing pipelines. It makes it easier for you to visualize and manage complex interactions. You might need a deeper understanding of graph theories, which could initially steepen your learning curve.

Why Start with LangGraph?

LangGraph is an open-source framework designed by Langchain to build stateful, multi-actor applications using LLMs. Inspired by the long history of representing data processing pipelines as directed acyclic graphs (DAGs), LangGraph treats workflows as graphs where each node represents a specific task or function.

This graph-based approach allows for fine-grained control over the flow and state of applications, making it particularly suitable for complex workflows that require advanced memory features, error recovery and human-in-the-loop interactions. LangGraph integrates seamlessly with LangChain, providing access to various tools and models and supporting various multi-agent interaction patterns.