STATEFUL WORKFLOWS / CHECKPOINTS / HUMAN APPROVAL
LangGraph Course
Build an AI workflow that knows its current state, pauses for a decision and resumes after a failure. This LangGraph Course focuses on controlled orchestration, combining ordinary program steps with model-driven decisions in a workflow you can inspect.
Course outline8 modules
Practice3 project scenarios
ScheduleDiscuss batch options
Course feeRequest current details
About the LangGraph Course
LangGraph provides a low-level runtime for stateful agent orchestration. Nodes perform work, edges control movement and shared state carries information between steps. The goal is to understand the lifecycle of a workflow, not simply connect more agents. You practise what happens when a tool fails, approval is declined or a process resumes after interruption.
The broad Generative AI course introduces agents; this course specialises in workflow control and durability. It is different from LangChain application integration and CrewAI role-based collaboration. Detailed RAG indexing, model training and general cloud administration are not the core syllabus.
For product-specific terminology and behaviour, use LangGraph overview. Match the documentation to the environment used in your exercises.
Who Should Join?
Python functions, type hints, exceptions and basic model API usage are expected. Familiarity with async code and persistence is useful. Complete a simple model-backed application before attempting checkpointing and recovery exercises.
Python AI developersMove beyond a single model call into multi-step controlled workflows.
Backend engineersDesign recoverable application state and side-effect boundaries.
Agent developersAdd approval, observability and bounded execution to an agent prototype.
For complementary learning, explore Generative AI Training. Choose the broader program if you need an introduction to AI models, prompting and the wider application landscape before specialising.
LangGraph Course Syllabus: 8 Practical Modules
Each module connects a concept to an exercise and an output you can explain. Work through the foundations before attempting the integrated project.
1. Workflow modelling and boundaries
Describe a business task as explicit states and transitions. Identify which steps need a model and which should remain deterministic. Produce a state diagram with success, rejection, timeout and escalation paths before writing the graph.
2. State, nodes and edges
Define a typed state structure and build small nodes with clear contracts. Add edges and conditional routing. Inspect how state changes after each node and ensure parallel updates use a deliberate merge strategy rather than silently overwriting information.
3. Model and tool nodes
Integrate a model decision with validated tool inputs. Keep business rules outside the prompt where code can enforce them. Restrict available tools and test what happens when the model asks for an unsupported action or provides incomplete arguments.
4. Checkpoints and conversation threads
Persist workflow progress with a checkpointer suitable for the lab. Use separate thread identifiers and understand what a saved checkpoint contains. Demonstrate resuming one workflow without mixing its state with another user session.
5. Human approval and interrupts
Pause before a consequential action and present the proposed change for review. Implement approve, reject and revise paths. Record the decision in state and show that a rejected action does not execute when the workflow continues.
6. Recovery and bounded execution
Handle failed tools, timeouts and repeated routing. Set practical execution limits and design idempotent side effects so a retry does not duplicate an action. Test recovery from a checkpoint using a mock service with a deliberate failure.
7. Subgraphs, streaming and inspection
Break a larger workflow into understandable components. Stream progress messages without leaking private state. Inspect execution traces and compare the expected route with the observed route for normal, rejected and failed requests.
8. Deployment-ready capstone
Package the graph with configuration, tests and state-storage notes. Define cleanup, access and retention responsibilities. Present an approval-based workflow with evidence of isolation, recovery and termination; explain remaining production work honestly.
Discuss Your Learning Goals
Tell the team about your experience and preferred schedule. Book a free demo to discuss the course, lab access and the practical work expected from you.
Practical Skills You Will Develop
Use the exercises to build an explanation as well as a result. You should be able to show what you did, how you checked it and where the limits are.
State designDefine what a workflow knows and how its state changes.
Conditional routingMake success, rejection and escalation paths explicit.
Safe resumptionResume saved work without confusing sessions or duplicating side effects.
Human oversightPlace review before consequential actions and preserve the decision.
Recovery testingExercise failures and bounded retries rather than only the happy path.
Trace-based debuggingExplain the path a workflow took and why it took it.
Tools and Lab Requirements
Use a personal practice environment with synthetic or openly licensed data. Keep credentials outside notebooks and source control. Confirm software access, hardware and any paid API usage with the course team before enrolling.
Python and LangGraphUse a pinned environment and the matching reference documentation.
State persistenceBegin with a lab checkpointer and discuss durable storage requirements separately.
Mock tools and tracesUse synthetic requests and sandboxed actions with inspectable execution evidence.
Consult LangGraph persistence during practice. Use documentation matching the installed version and check applicable permissions and service costs.
Your Learning Roadmap
Build confidence in stages. Practice time and your starting knowledge matter as much as the number of scheduled sessions.
1. Set up and understandCheck the prerequisites and lab access. Complete the first two modules and explain the basic workflow in your own words.
2. Build and investigateWork through the middle modules. Keep notes of errors, what you tried and the evidence that supported a fix.
3. Test and presentComplete the final modules and an integrated scenario. Present your output, validation and a short handover guide.
3 Practical Project Scenarios
These are teaching scenarios using approved lab systems and synthetic data. They are not claims about live client work or previous student results.
Approval-based service requestRoute a fictional request through validation, drafting and human approval. Reject incomplete requests and block execution when approval is denied.
Recoverable research workflowSave progress across collection, summarisation and review. Resume after a simulated source failure without repeating completed side effects.
Support escalation graphClassify a synthetic ticket, attempt a permitted lookup and route low-confidence or failed cases to a human queue with a clear reason.
How the Skills Work in Practice
A workflow prepares an account-change request in a sandbox. A deterministic node validates the requested fields, a model drafts an explanation and an interrupt waits for approval. Only a later node can call the mock update tool.
Now simulate a timeout after the mock service receives the request. The recovery exercise must prevent a duplicate update. Use a stable action identifier and an idempotent tool contract, then explain why checkpointing alone does not make every external action safe to repeat.
Why Learn with Brolly Academy?
Choose a course that connects the subject to work you can actually demonstrate. Use a demo to discuss the learning path and decide whether it fits your starting point.
A connected learning pathThe eight-module outline moves from foundations to an integrated task. Each module identifies an output rather than leaving practice as a vague promise.
Discuss your own learning goalShare your experience and preferred format with the course team. Use a demo to assess whether the technical depth, pace and project expectations fit your needs.
Clear course boundariesThe page explains prerequisites, product scope and the difference between training completion and independent certification. You can compare the offer with your actual requirements.
Compare Brolly Academy with Other Training Institutes
Compare the same evidence from each provider: what you will build, what you will test and which services the fee includes. Ask for specific examples rather than relying on broad claims about advanced AI.
What to discuss with Brolly AcademyReview these eight modules and the three project scenarios.
Ask for the assigned trainer profile.
Check the lab version and access period.
Review the fee, schedule and certificate terms.
Use the demo to assess the teaching approach.
What to check with any instituteRequest a detailed outline, not just product names.
Verify the trainer information supplied.
Separate demonstrations from your own lab work.
Check licences, exam costs and refund conditions.
Compare the total commitment, not only the advertised price.
Classroom, Online and Corporate Learning
Discuss the currently available delivery format with the academy before booking. Batch availability and session timings should be agreed in writing.
Classroom learning enquiryConfirm the venue, next available batch and computer requirements before arranging travel.
Live online enquiryCheck the session time zone, remote lab access and arrangements for asking questions or catching up on a missed session.
Corporate team enquiryShare your team size, current tools and learning objectives. Agree a scoped program without sharing confidential business data.
For a team program, explore Brolly Academy corporate training.
LangGraph Course Fee and Duration
Contact Brolly Academy for the current fee, available delivery format and batch timetable. Discuss your starting skills and the practical work you want to complete before choosing a batch.
Request the current course feeAsk for the complete written quotation, taxes, payment terms and refund conditions. Confirm whether API usage, cloud compute, software plans or external examinations are separate.
Confirm the learning scheduleAsk about instructor-led hours, independent practice, project review and the access period. Eight modules describe the learning sequence, not a fixed completion time.
Before you enrolCheck lab access, materials, project feedback, missed-session arrangements, refund terms and any additional charges. Keep a copy of the agreed offer.
Course Completion and Certification Guidance
Brolly Academy course completion recognizes the training and assessment work agreed for your batch. It is separate from a credential awarded by a software vendor or another certification body.
Brolly Academy course completionAsk for the attendance, assignment and assessment requirements, the certificate wording and how completion will be verified.
Independent certificationUse official vendor information to check whether a relevant credential is currently offered and what preparation it requires. No vendor authorization, exam voucher or pass guarantee is implied.
Career Roles and Skill Applications
Match the learning path to a role, then compare its requirements with your existing experience. The course can support skill development; it does not guarantee employment.
Agent workflow developerImplement inspectable, stateful AI workflows.
AI platform engineerManage workflow execution, persistence and recovery boundaries.
Backend automation engineerCombine deterministic business logic with controlled model decisions.
You can also explore AI Testing Training. Develop a deeper QA practice for AI answers, tool behaviour and release decisions.
Where These Skills Are Used
Stateful orchestration is useful when a task spans several steps, depends on review or must survive an interruption. It adds complexity, so a short deterministic script may still be the better choice for a simple fixed task. Architecture decisions are part of the learning outcome.
Interview and Portfolio Preparation
Prepare evidence you can discuss clearly. Label practice work as training work and do not present a teaching scenario as paid client experience.
Explain a projectDescribe the requirement, your decisions, the result and one limitation. Be ready to answer what you would change for a real deployment.
Show useful evidenceKeep approved files, test results and a concise README or runbook. Remove secrets and private information before sharing a portfolio.
Discuss support servicesAsk the academy which resume, mock-interview or job-search services are included in your batch. Placement assistance is not a job or salary guarantee.
Career Planning and Salary Expectations
Salary depends on the role, prior experience, location and the employer. A tool course alone does not establish a salary band. Compare recent job descriptions, required experience and responsibilities rather than relying on a headline income promise.
Meet the Trainer Through a Demo
Request the assigned trainer profile for this specialist subject. In a demo, ask how the trainer would investigate a practical LangGraph failure and review a learner's project evidence.
Relevant experienceAsk for examples of work with LangGraph that can be discussed without revealing confidential client information.
Practical explanationAsk the trainer to explain a failure scenario and how a learner would investigate it, rather than only showing a finished result.
Feedback and supportDiscuss how assignments are reviewed, how questions are handled and the support period included in the course.
Brolly Academy Learner Feedback
Read available academy feedback and ask whether a review relates to this particular course, trainer and delivery format. General academy reviews should not be mistaken for verified results from this new course.
Read Academy ReviewsDownload Your Practice Checklists
Use these editable CSV files to organize your learning. They open in common spreadsheet tools and contain real module and project-checklist content.
Download Syllabus (CSV) Project Checklist (CSV)Official Documentation for Further Reading
Use the documentation that matches your product version and environment. These sources support technical learning; linking to them does not imply endorsement of Brolly Academy.
Related Courses at Brolly Academy
Choose complementary learning based on your current skill gaps. These are separate courses, not automatically included in this program.
Generative AI TrainingChoose the broader program if you need an introduction to AI models, prompting and the wider application landscape before specialising.
View Generative AI Training
Agentic AI CourseExplore agent architecture and decision-making across a broader range of tools.
View Agentic AI Course
AI Testing TrainingDevelop a deeper QA practice for AI answers, tool behaviour and release decisions.
View AI Testing Training
Talk to the LangGraph Course Team
Call +91 81868 44555 or send a course enquiry to discuss the syllabus and current batch options. For a classroom visit, confirm the venue and appointment with Brolly Academy before travelling.
Read our contact details for the academy location and enquiry options. Online delivery, session time zones and tool access should be confirmed for your batch.
Call +91 81868 44555LangGraph Course FAQs
Do I need LangChain before LangGraph?
You need model and tool integration basics, but LangGraph can be used independently of LangChain. This course assumes you can already build a small Python application that calls a model.
Is every LangGraph workflow an autonomous agent?
No. A graph can combine predictable program steps with selected model-driven decisions. The design should use autonomy only where the task benefits from it.
What is a checkpoint?
It is saved workflow state that supports inspection and resumption. Its exact content and storage behaviour depend on the configured implementation; it is not a substitute for an application data-backup strategy.
Does resuming guarantee no duplicate actions?
No. External side effects need their own idempotency and recovery design. A retry can repeat a request, so the course tests this boundary using a mock service.
How is this different from CrewAI?
This course centres on graph state, routing and execution control. CrewAI training centres on organising agents, tasks and crews. They can solve related problems but encourage different implementation choices.
Will the workflow send real messages during practice?
The core approval exercises use mock actions. Real sends or production changes require explicit permission, suitable credentials and an approved environment; they are not required to demonstrate the design.
How much does the LangGraph Course cost?
Contact Brolly Academy for the current quotation. Ask for the total payable, taxes, payment terms, lab access and any separate API, compute or subscription charges. The outline does not imply an external exam voucher or paid tool licence.
What is the course duration and batch schedule?
The eight modules describe the learning sequence, not a fixed number of days. Ask the team to confirm instructor-led hours, practice expectations, batch dates and the support period for your starting level.
Can I attend a free demo before enrolling?
Use Book Free Demo to open the enquiry form, or contact the team on WhatsApp. Share your experience and learning goal so the counsellor can discuss a suitable session and current availability.
What certificate will I receive?
Discuss the Brolly Academy course-completion requirements for your batch, including attendance, assignments and project assessment. Course completion is separate from any credential issued by a software vendor or independent examination body.
Does the course guarantee a job or salary?
No. The learning path is designed to build demonstrable skills. Ask which portfolio, resume or interview-support services are included. Hiring decisions depend on your wider experience, preparation, location and employer requirements.
How should I compare this course with another institute?
Compare the actual syllabus, your own lab work, trainer experience, project feedback, tool costs and written terms. Ask each provider the same questions and use a demo to assess the teaching style before committing.