AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
Multi-Agent Systems
Create teams of agents with defined roles, shared state and controlled hand-offs.
Online + OfflineWeekdays + WeekendsRegular + Fast Track
22+years in training
20,000+learners across TGC
5classroom locations
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Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Build teams of specialised AI agents with defined roles, shared state, structured hand-offs and human approval.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
Multi-Agent Systems DeveloperAgentic AI EngineerAI Orchestration DeveloperLLM Systems Engineer
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You already build Python agents
You need specialised workers and controlled hand-offs
You want orchestration, testing and operating practice
YOUR LEARNING ARC
From guided foundation to finished work.
Design
Define roles, tasks, state and dependencies.
Contract
Build tools and structured agent hand-offs.
Orchestrate
Coordinate routing, parallel work and approval.
Operate
Evaluate, deploy and monitor the full system.
INDUSTRY TASKS
Practise the work, not only the tool.
- Build a supervisor-and-specialist workflow
- Create a multi-agent research system
- Test and deploy an operations agent team
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Choose a suitable multi-agent design
A role, task, state and dependency architecture.
02
Build controlled agent hand-offs
A working system using structured contracts and approved tools.
03
Add knowledge and human decisions
A cited workflow with permissions and approval points.
04
Evaluate and operate agent teams
A deployed capstone with traces, tests and cost records.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
5 learning modules
Design and build teams of specialised AI agents with shared state, controlled hand-offs, testing and human approval.
Multi-agent foundations and use-case design
Decide when several agents are justified and define the work each one should own.
CORE TOPICS
- Single agent, workflow and multi-agent comparison
- Role, goal and responsibility boundaries
- Task decomposition and dependency mapping
- Cost, delay and failure-risk assessment
GUIDED PRACTICE
Compare possible architectures for a research or operations brief and select the simplest workable design.
MODULE DELIVERABLE
Multi-agent use-case and architecture brief
Agents, tools and structured contracts
Build specialised workers that exchange dependable information rather than loose chat messages.
CORE TOPICS
- System instructions and role prompts
- Tool schemas and permission limits
- Structured input and output contracts
- Validation, retries and fallback paths
GUIDED PRACTICE
Create two agents with controlled tools and a typed hand-off between them.
MODULE DELIVERABLE
Contract-based agent pair
Orchestration with LangGraph and CrewAI
Coordinate routing, sequencing and parallel work using current agent frameworks.
CORE TOPICS
- Supervisor, router and specialist patterns
- Graphs, nodes, edges and state
- Sequential, parallel and conditional execution
- Framework comparison and architecture portability
GUIDED PRACTICE
Build the same small system using a selected orchestration pattern and inspect every transition.
MODULE DELIVERABLE
Orchestrated multi-agent workflow
Memory, retrieval and human approval
Manage shared context while keeping knowledge, access and decisions under control.
CORE TOPICS
- Short-term state and task records
- Retrieval from approved knowledge
- Agent-to-agent context limits
- Approval, escalation and intervention points
GUIDED PRACTICE
Add cited knowledge and an approval gate before a high-impact action.
MODULE DELIVERABLE
Supervised knowledge-agent system
Evaluation, operations and capstone
Test the whole system for task success, hand-off errors, cost and unsafe behaviour.
CORE TOPICS
- End-to-end test cases and scoring
- Loop, conflict and incomplete-task detection
- Tracing, logs, latency and cost
- Deployment, monitoring and incident fallback
GUIDED PRACTICE
Deploy and present a multi-agent capstone with evaluation records and operating guidance.
MODULE DELIVERABLE
Deployed multi-agent capstone
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
Guided practice brief
Plan, produce, test and present a finished piece with trainer feedback.
Individual application
Plan, produce, test and present a finished piece with trainer feedback.
Workflow build
Plan, produce, test and present a finished piece with trainer feedback.
Industry-style assignment
Plan, produce, test and present a finished piece with trainer feedback.
Quality review
Plan, produce, test and present a finished piece with trainer feedback.
Final capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
CrewAILangGraphPythonOpenAI API
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
Is this an advanced course?
Yes. Learners should already understand Python, APIs and basic agent architecture.
＋Which frameworks are used?
Guided work uses current tools such as LangGraph and CrewAI while teaching patterns that transfer across frameworks.
＋How are agent loops controlled?
Stopping rules, state limits, timeouts, approval and test cases are included in every major build.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or live online. Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Yes. Course completion requires attendance, assignments and the final project.
＋Can working professionals join?
Yes. Weekday, weekend and selected fast-track schedules are available.
＋NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.