Data Science & AI
Agentic AI Course
Hands-on agentic AI engineering: frameworks, multi-step workflows, memory and production practices
- Duration
- Live batches
- Format
- Live online
- Modules
- 10 modules
- Certificate
- On completion
- ✓Live online instructor-led training in scheduled batches
- ✓Build single-agent and multi-agent systems with current orchestration frameworks
- ✓Stateful workflows with branching, retries and human approval steps
- ✓RAG, memory and MCP-based tool integration
- ✓Evaluation, observability and cost control for agents in production
- ✓Assure Success course-completion certificate after a capstone agent
About the course
What this course covers
The Agentic AI Course is a deeper, framework-oriented companion to our shorter Applied Agentic AI course. It is for developers who want to design agent systems that handle real, multi-step work such as research, document processing, customer-support triage, data analysis and internal workflow automation.
You begin with the agent loop and then move to orchestration frameworks that let you define stateful graphs of steps, with branching, parallel work, retries and checkpoints. You build retrieval and memory layers, integrate tools and data through the Model Context Protocol, and design multi-agent teams with clear roles and hand-offs. The course spends significant time on what separates demos from products: evaluation sets, tracing, guardrails, permissions, human-in-the-loop design, latency and cost.
Frameworks in this area change quickly, so labs concentrate on patterns that stay valid, with specific libraries used as current examples. There is no external exam; you complete a capstone and receive an Assure Success course-completion certificate.
Who should attend
- ● Software and backend engineers building AI-powered automation
- ● ML and data engineers moving into LLM application work
- ● Solution architects designing AI workflows for enterprises
- ● Developers who completed an introductory generative AI or agent course
- ● Technical founders prototyping agent-based products
Prerequisites
- Comfortable Python programming, including APIs and JSON
Key skills
Skills you will walk away with
Agent architecture
Choose between workflows, single agents and multi-agent systems for a given task.
Stateful orchestration
Model processes as graphs with state, branching, loops and checkpoints.
Tool and API integration
Design robust tools with clear schemas, timeouts and error messages.
RAG and memory
Combine retrieval, summarisation and long-term memory for grounded agents.
MCP integration
Connect agents to external tools and data sources using the Model Context Protocol.
Human-in-the-loop design
Insert approvals, escalations and review queues where risk is high.
Curriculum
Module-by-module syllabus
10 modules · 40 topics
1Module 1: Agentic Systems Overview4 topics ▾
Learning objective: Frame the design space.
- ▸ Workflows vs agents
- ▸ Reasoning models and tool-use basics
- ▸ Typical enterprise use cases
- ▸ Risk and failure modes
2Module 2: Core Agent Loop in Python4 topics ▾
Learning objective: Build the loop from first principles.
- ▸ Tool schemas and calling
- ▸ Planning and reflection
- Stop conditions and budgets
Schedules
Upcoming live batches
Enroll now and choose your batch dates
Send an enquiry and we'll reserve your seat in the next batch.
Certification
How you get certified
- 1Enrol in a scheduled live batch and complete the environment and API setup
- 2Attend sessions and complete the labs
- 3Build the capstone agent and present evaluation results
- 4Meet the attendance and assessment criteria for the batch
- 5Receive your Assure Success course-completion certificate
Career outcomes
Roles this opens up
Agentic AI Engineer
₹8–22 LPA (approx.)Designs and ships multi-step AI agents and workflows.
AI Solutions Developer
₹7–20 LPA (approx.)Implements AI automation for client or internal use cases.
LLM Application Engineer
₹8–22 LPA (approx.)Builds RAG, tool-use and assistant features in products.
AI Solution Architect (associate)
₹14–30 LPA (approx.)Defines agent architectures, guardrails and integration patterns.
Salary ranges are approximate figures for India and vary by city, company and experience.
Why this certification is worth it
Production-oriented
Evaluation, tracing and guardrails are taught alongside building.
Pattern over library
Why Assure Success
Learn it once, pass it once
Trainers from the field
Every session is led by a practitioner who uses this material at work.
Batches that fit your week
Weekday and weekend batches in IST, scheduled for working professionals.
Exam-style practice
Practice questions and, where available, a full simulator free with the course.
Exam voucher help
Discounted vouchers and step-by-step help booking your exam.
Human support
WhatsApp support Mon–Sat, 9 AM–8 PM IST — a person answers.
Pay your way
UPI, cards, netbanking and EMI in India; international cards accepted.
FAQs
Questions learners ask us
Q.Which framework will be taught?
We use current popular orchestration libraries as examples, but teach the underlying patterns so that you can switch frameworks. The coordinator can share the current lab stack for your batch.
Q.How is this different from Applied Agentic AI?
Applied Agentic AI is a short build-focused course. This course goes deeper into orchestration frameworks, multi-agent design, governance and a larger capstone.
Q.Do I need a paid LLM account?
Labs aim to use free tiers or open models where possible. Any paid usage requirement is communicated before the batch.
Q.Is coding mandatory?
Yes. Python is used throughout. For no-code options see the No-Code AI Agents course.
Q.Is there an exam?
No external exam. You get an Assure Success course-completion certificate.
Q.Are there jobs in agentic AI in India?
AI engineering roles that include agent and RAG work are growing in product companies, services firms and startups. We cannot promise placement, but the skills map well to those roles.
Will we deploy to the cloud?
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₹31,999
Agentic AI Course