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Training LangGraph - Building Multi-Step AI Agents

Course created on July 27, 2026Updated on October 5, 2026

On quote$2,310

2 days
Onsite
10 people max.

Request a quote See the program

Ref: BVR253

10 people max.

On quote$2,310

In-company rate: on quotefrom $4,190 for the whole team

On-site and certification exam on quote

2 days

Onsite

Don't let this gap widen

Why this program matters

Without LangGraph mastery, AI workflows remain linear and fragile, causing 50% time lost to manual debugging according to LangChain studies.
Companies without graph-based agents suffer 3x more production failures, with error costs nearing 20k€ per major incident.
In 2024, 68% of AI recruiters reject profiles limited to simple chains, widening the competitive gap.
Every quarter without LangGraph skills exposes your team to obsolescence against autonomous solutions that boost productivity by 40%.

Trusted by — schools, companies and industrial groups

25,750 programs · 25 countries

Every program built with a dedicated engineer

Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.

Learning objectives

Master the fundamentals of LangGraph to develop professional AI applications
Build agent graphs with nodes, edges, and routing conditions
Implement state persistence and memory in complex workflows
Integrate external tools and LLM models for intelligent agents
Deploy scalable LangGraph applications in a certified enterprise environment
Optimize graph performance for real-world use cases

Program

Module 1LangGraph Fundamentals: Installation and First Stateful Graphs (Python, LangChain, LLM Tools)

Quick installation of the LangGraph environment with pip and setup of a first professional project, discovery of key concepts like nodes, edges, and shared state, creation of a simple graph for a question-answering agent, practical exercises on concrete business cases with integration of OpenAI or Hugging Face models, interactive debugging, and production of a first functional deliverable ready to scale.

Module 2Advanced LangGraph Agents: Memory, Tools, and Deployment (Persistence, API, Streamlit)

Development of multi-step agents with conditional routing and dynamic loops, addition of persistent memory via checkpoints and lightweight databases, integration of external tools like web search or calculators for hybrid tasks, testing in real conditions on business scenarios such as customer automation, deployment of a complete application with Streamlit or FastAPI, performance optimization, and delivery of a certified ongoing project with annotated source code.

Evaluation method

Multiple-choice quiz to validate acquired knowledge at the end of the training
Continuous evaluation through practical exercises on graphs
Defense of the ongoing LangGraph project in front of the trainer

Learning method

Courses led by an expert AI trainer in active practice
Practical exercises on real business cases with LLMs
Progressive ongoing project throughout the training
Complete course materials provided to each participant

Methods, materials and delivery

The Training LangGraph - Building Multi-Step AI Agents program is delivered onsite or remote (blended-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training LangGraph - Building Multi-Step AI Agents program, the following equipment is required:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, hands-on exercises and complementary resources
Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training LangGraph - Building Multi-Step AI Agents program is performed through:

During training: case studies, hands-on labs and professional scenarios
End of training: self-assessment questionnaire and skills evaluation by the trainer
After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.

The Learni story

Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.

Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

Triple validation: technical, pedagogical, sectoral.
Minimum rating 4.8/5 over the last 12 sessions.

Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

Live briefing on goals and team context.
Veto right — we swap the trainer for free if needed.

Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

Hands-on cases drawn from your stack and projects.
Program co-written then validated by your team.

Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

NPS, knowledge quizzes and skills self-assessment.
Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

A child walking to school with a backpack

Our social commitment

A school kit donated to a child for every training booked

To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.

Backpack, notebooks and essential supplies
Distributed through our partner charities
Included, at no extra cost to you

Enroll and offer a kit

FAQ

Frequently asked questions

Which tools are used in LangGraph training?+

Hands-on work runs on python, langChain, LLM Tools, persistence, API and streamlit. Those tools come from the LangGraph program itself, delivered on site over 2 days, so participants practise on the stack they will use at work.

What can participants do after LangGraph training?+

They can master the fundamentals of LangGraph to develop professional AI applications, build agent graphs with nodes, edges, and routing conditions and implement state persistence and memory in complex workflows. Those are the stated objectives of the LangGraph program at Intermediate level, checked by the end-of-session assessment.

What does the LangGraph program cover, day by day?+

Day 1: LangGraph Fundamentals: Installation and First Stateful Graphs (Python, LangChain, LLM Tools). Day 2: Advanced LangGraph Agents: Memory, Tools, and Deployment (Persistence, API, Streamlit). The LangGraph program runs over 2 days, delivered on site.

How is LangGraph training assessed?+

Assessment relies on multiple-choice quiz to validate acquired knowledge at the end of the training, continuous evaluation through practical exercises on graphs and defense of the ongoing LangGraph project in front of the trainer. Learni issues a completion certificate together with the individual assessment report at the end of the LangGraph program, which an L&D team can file as evidence.

How much does LangGraph training cost per participant?+

LangGraph training is priced on quote. The amount depends on headcount, format and how far the syllabus is tailored to your team. A detailed quote is sent within one business day, and team pricing covers the whole group from the second participant.LangGraph training costs $2,310 per participant. For an in-company team, the flat rate starts at $4,190 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.

How long does LangGraph training take?+

2 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.

Who pays for LangGraph training?+

Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.

What do participants need to know before LangGraph training?+

Basic knowledge of Python and introductory concepts of LangChain.

Is a certificate issued after LangGraph training?+

Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.

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