Data Science & AI
Applied Agentic AI Training
Design and build AI agents that plan, call tools and complete multi-step tasks, in 16 focused live hours
- Duration
- 16 hours
- Format
- Live online
- Modules
- 8 modules
- Certificate
- On completion
- ✓16 hours of live online instructor-led training in scheduled batches
- ✓Build a working tool-using agent from a plain LLM API call
- ✓Planning, memory, retrieval and multi-agent patterns explained with code
- ✓Model Context Protocol (MCP) basics for connecting tools and data
- ✓Evaluation, cost control and guardrails for agentic systems
- ✓Assure Success course-completion certificate after a mini-project
About the course
What this course covers
Applied Agentic AI is a short, build-focused course on AI agents: systems where a language model decides which steps to take, calls tools such as search, databases or APIs, and loops until a task is done. Agents are powerful but easy to get wrong, so the course teaches both how to build them and how to keep them under control.
You start from a basic LLM API call and add structured outputs, then tool calling, then a planning loop. From there you add memory and retrieval, try simple multi-agent patterns, and connect tools through the Model Context Protocol. A good part of the 16 hours goes to the unglamorous but essential parts: testing agent behaviour, limiting loops and spend, handling failures, and deciding when a plain workflow is better than an agent.
There is no external exam. You finish with a small working agent and an Assure Success course-completion certificate.
Who should attend
- ● Python developers who want to build LLM-powered agents
- ● Data scientists and ML engineers extending into agentic workflows
- ● Automation and RPA professionals exploring AI-driven process automation
- ● Technical product managers and architects who need to judge agent designs
- ● Graduates with basic Python who completed a generative AI introduction
Prerequisites
- Working Python knowledge (functions, JSON, HTTP requests)
Key skills
Skills you will walk away with
Tool calling
Define tools with schemas, let a model choose them and handle results and errors.
Agent loops and planning
Implement reason-act loops with step limits and stopping conditions.
Memory and retrieval
Give agents short-term state and document retrieval for grounded answers.
Structured outputs
Get reliable JSON from models and validate it before acting.
Multi-agent patterns
Split work between specialised agents with a supervisor or hand-off pattern.
MCP basics
Expose and consume tools and data through the Model Context Protocol.
Curriculum
Module-by-module syllabus
8 modules · 32 topics · 16 hours
1Module 1: From LLM Calls to Agents4 topics ▾
Learning objective: Understand what makes a system agentic.
- ▸ Workflows vs agents
- ▸ Anatomy of an agent: model, tools, memory, loop
- ▸ Use cases and anti-patterns
- ▸ Setting up the LLM API
2Module 2: Structured Outputs and Tool Calling4 topics ▾
Learning objective: Make models act reliably.
- ▸ JSON schemas and validation
- ▸ Defining tools and parameters
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 API and environment setup
- 2Attend sessions and complete the lab for each module
- 3Build and demo the mini-project agent
- 4Meet the attendance and assessment criteria for your batch
- 5Receive your Assure Success course-completion certificate
Career outcomes
Roles this opens up
AI Agent Developer
₹7–20 LPA (approx.)Builds tool-using agents and assistants for business tasks.
Generative AI Engineer
₹7–20 LPA (approx.)Implements LLM features including RAG and agent workflows.
Automation Engineer (AI-enabled)
₹5–14 LPA (approx.)Extends traditional automation with LLM decision steps.
Technical Product Manager (AI)
₹12–28 LPA (approx.)Scopes agent products and weighs their risks and costs.
Salary ranges are approximate figures for India and vary by city, company and experience.
Why this certification is worth it
Short and practical
A 16-hour course that ends with something running.
Realistic about limits
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.What is an AI agent in simple terms?
An AI agent is a program in which a language model decides what to do next, uses tools such as search or databases, looks at the results and repeats until it finishes the task.
Q.How is this different from the Agentic AI Course?
This is a compact 16-hour build course. The Agentic AI Course goes further into frameworks and multi-step workflows.
Q.Do I need to know machine learning?
No. You need Python and a basic idea of how LLMs are prompted.
Q.Will I pay for LLM usage?
Labs are designed for free tiers or low-cost usage. The coordinator will share the exact requirements before the batch.
Q.Is there an exam?
No. You receive an Assure Success course-completion certificate after the mini-project.
Q.Are agents reliable enough for business use?
They can be for narrow, well-tested tasks with guardrails and human review. The course teaches how to decide that and how to test for it.
Q.Which agent framework will we use?
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₹59,999
Applied Agentic AI Training