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Data & AI Training

AI Agents

Design and build AI agents that use tools, plan multi step tasks, keep memory and work within guardrails, from simple assistants to workflow agents.

IntermediateAI & DataSoftware Development

At a glance

  • CategoryData & AI Training
  • LevelIntermediate
  • Curriculum6 modules, 4 project ideas
  • InstituteAIIT Roorkee, Roorkee

Course Overview

About this course

An AI agent uses a language model to decide which steps to take and which tools to use in pursuit of a goal, such as researching a topic, updating a spreadsheet or triaging support requests.

This course teaches how to design, build and test agents with Python: the agent loop, tool design, planning, memory, connecting to external systems through APIs and protocols such as MCP, human approval steps, error handling, evaluation and safety.

Learning Objectives

By the end of AI Agents, learners should be able to:

  • Explain the agent loop of reasoning, acting and observing
  • Design safe, well described tools for agents
  • Build agents that plan and complete multi step tasks
  • Add memory, human approval and error recovery
  • Evaluate agent behaviour and limit risk

Topics Covered

01Agent foundations
  • Assistants, workflows and agents
  • The agent loop
  • When not to use an agent
02Tools
  • Function calling
  • Tool descriptions and schemas
  • Connecting APIs and data
03Planning and control
  • Task decomposition
  • Routing and branching
  • Stopping conditions
04Memory and context
  • Short and long term memory
  • Context management
  • Retrieval for agents
05Integration
  • Model Context Protocol basics
  • Browser and file tools
  • Human in the loop approvals
06Reliability and safety
  • Evaluating agents
  • Permissions and sandboxing
  • Logging and observability

Topic order and depth may be adjusted for the batch, format and learner level.

Practical Learning

Every module pairs explanation with hands-on work. Typical practical activities in this course:

Building an agent loop from scratch before using frameworks

Tool design reviews

Failure injection tests

Agent evaluation with scripted tasks

Representative Projects

Projects are chosen with mentors based on your level and interests. Examples include:

  • Research assistant agent that cites sources
  • Email or ticket triage agent with approval step
  • Spreadsheet and report automation agent
  • Personal study planner agent

Who Should Join

  • Python developers
  • LLM application developers
  • Automation engineers
  • Students building advanced AI projects

Prerequisites

  • Python programming
  • Experience with LLM APIs or completion of LLM Applications recommended

Learning Format

This course can be offered in the following formats, depending on the batch:

  • Short-Term Courses
  • Long-Term Courses
  • Certification-Oriented Programs
  • Weekend Programs
  • Workshops
  • Live Project Training
  • Internship Programs

Ask the team for current batch timings and the formats open for AI Agents.

Career Relevance

Skills from this course are relevant to roles and directions such as:

  • AI Agent Developer
  • AI Engineer
  • Automation Engineer
  • AI Solutions Developer

Career relevance describes where these skills are commonly used. It is not a promise of employment. Learners can use AIIT Roorkee's placement assistance for career preparation support.

FAQs

What is the difference between AI Agents and Agentic AI courses?

AI Agents focuses on building individual agents with tools, memory and guardrails. Agentic AI looks at larger agentic systems: multi agent designs, orchestration, governance and deploying agents inside real workflows.

Which frameworks are covered?

You first build an agent without a framework to understand the mechanics, then use popular agent frameworks. Specific frameworks are chosen based on current industry use.

Are AI agents safe to use in real systems?

They can be useful when designed carefully with limited permissions, human approvals for important actions, testing and monitoring. These practices are a core part of the course.

What is the duration and schedule of this course?

Duration, batch timings and format are shared when you enquire, because they depend on whether you choose a short-term, long-term, weekend or training format. Contact the team by phone, WhatsApp or email for current batches.

Is placement assistance available?

Learners can use AIIT Roorkee's placement assistance, which includes career counselling, CV preparation, LinkedIn development, interview preparation and mock interviews. Placement assistance is career preparation support and does not constitute a guarantee of employment or placement.

Practical Lab Environment

AI Agents Developer Console

Start Learning AI Agents

Build practical engineering skills with 1-on-1 mentorship and live projects at AIIT Roorkee.

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