AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
Agentic AI Developer Program
Design and build AI agents that reason through tasks, use tools, retrieve knowledge and work with approval gates.
Online + OfflineWeekdays + WeekendsRegular + Fast Track
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Build AI systems that plan a task, call approved tools, retrieve information, maintain working state and stop for human approval when needed.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
Agentic AI DeveloperAI Application EngineerAutomation EngineerLLM Engineer
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You can already work with Python and APIs
You want to move beyond chat interfaces
You need production patterns for tool use and approval
YOUR LEARNING ARC
From guided foundation to finished work.
Architecture
Define state, tools, roles and stopping rules.
Knowledge
Add retrieval, memory and source controls.
Orchestration
Build agent loops and controlled hand-offs.
Operations
Evaluate, deploy and monitor the system.
INDUSTRY TASKS
Practise the work, not only the tool.
- Connect an agent to approved APIs
- Build a cited knowledge agent
- Run and evaluate a multi-agent workflow
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
Design controlled agent architecture
A state, tool, permission and approval specification.
02
Implement reliable tool use
A working Python agent with validation and failure handling.
03
Ground answers in approved knowledge
A cited retrieval agent with access boundaries.
04
Evaluate and operate an agent system
A deployed capstone with tests, logs and fallback procedures.
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
Build production-minded AI agents that use tools, retrieve knowledge, maintain state and pause for human approval.
Agent architecture and control flow
Understand when an agent is useful and design its goal, state, tools and stopping rules.
CORE TOPICS
- Agent versus workflow versus chatbot
- State machines, loops and task decomposition
- Roles, permissions and stopping conditions
- Human approval and escalation design
GUIDED PRACTICE
Map an agent for a real process and identify unsafe or unnecessary autonomy.
MODULE DELIVERABLE
Agent architecture specification
Python, APIs and structured tool use
Give an agent dependable access to approved functions and external systems.
CORE TOPICS
- Model APIs, structured output and streaming
- Function calling and tool schemas
- Authentication, retries and rate limits
- Logging and deterministic fallbacks
GUIDED PRACTICE
Connect an agent to two controlled tools and handle invalid inputs and API failure.
MODULE DELIVERABLE
Tool-using service with error paths
Retrieval, memory and context
Ground agent decisions in approved knowledge while controlling what is remembered.
CORE TOPICS
- Embeddings, chunking and vector search
- RAG pipelines and source citations
- Short-term state and long-term memory
- Access boundaries and context hygiene
GUIDED PRACTICE
Build a knowledge agent that answers with sources and declines unsupported questions.
MODULE DELIVERABLE
Cited knowledge agent
Orchestration and multi-agent systems
Coordinate specialised workers without losing visibility or control.
CORE TOPICS
- Supervisor, router and specialist patterns
- LangGraph and CrewAI implementation
- Shared state and hand-off contracts
- Parallel work, conflicts and completion checks
GUIDED PRACTICE
Create a small multi-agent research or support system and inspect every hand-off.
MODULE DELIVERABLE
Orchestrated multi-agent application
Evaluation, deployment and operations
Test behaviour under normal and difficult conditions and prepare the system for real use.
CORE TOPICS
- Task success and tool-use evaluation
- Prompt injection and permission tests
- Cost, latency and observability
- Deployment, monitoring and incident fallback
GUIDED PRACTICE
Run a structured evaluation set, repair failures and deploy the final capstone with operating notes.
MODULE DELIVERABLE
Deployed agent capstone and evaluation report
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
Support agent
Plan, produce, test and present a finished piece with trainer feedback.
Research team
Plan, produce, test and present a finished piece with trainer feedback.
Lead qualification agent
Plan, produce, test and present a finished piece with trainer feedback.
Operations copilot
Plan, produce, test and present a finished piece with trainer feedback.
Knowledge assistant
Plan, produce, test and present a finished piece with trainer feedback.
Multi-agent 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
OpenAI APILangGraphCrewAIn8nPythonVector DB
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
How much Python is required?
You should be comfortable with functions, packages, APIs and basic data handling.
＋Which agent framework is taught?
Labs use current frameworks such as LangGraph and CrewAI, with architecture taught separately from any one library.
＋Do projects include safety controls?
Yes. Permissions, failure paths, human approval and evaluation are built into the projects.
＋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.