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Data & AI Training

Agentic AI

Go beyond single agents: multi agent systems, orchestration, long running workflows, evaluation, governance and deploying agentic AI in real organisations.

AdvancedAI & DataResearch

At a glance

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

Course Overview

About this course

Agentic AI describes systems where AI agents take goal directed actions with a degree of autonomy, often coordinating with other agents, tools and people across longer workflows.

This advanced course covers agentic architecture patterns, multi agent collaboration, orchestration and state, long running and scheduled workflows, integration with business systems, evaluation of complex behaviour, cost and latency, governance, security and the organisational questions of deploying autonomous systems responsibly.

Learning Objectives

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

  • Compare agentic architecture patterns and choose the right one
  • Design multi agent systems with clear roles and handoffs
  • Build stateful, long running agentic workflows
  • Evaluate and monitor agentic systems in operation
  • Apply governance, security and human oversight practices

Topics Covered

01Agentic systems
  • Levels of autonomy
  • Workflows vs agents
  • Architecture patterns
02Multi agent design
  • Roles and specialisation
  • Orchestrator and worker patterns
  • Communication and handoffs
03State and orchestration
  • Graph based workflows
  • Checkpoints and recovery
  • Scheduling and triggers
04Enterprise integration
  • Connecting business tools
  • MCP servers
  • Identity and permissions
05Evaluation and operations
  • Trajectory evaluation
  • Monitoring and tracing
  • Cost and latency optimisation
06Governance
  • Risk assessment
  • Human oversight
  • Policy, audit trails and responsible deployment

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:

Architecture design reviews

Multi agent build sprints

Chaos and failure testing

Governance case studies

Representative Projects

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

  • Multi agent research and report pipeline
  • Operations workflow with orchestrator and specialist agents
  • Agentic customer onboarding prototype with approvals
  • Evaluation and governance plan for an agentic system

Who Should Join

  • Developers experienced with LLM applications or agents
  • AI engineers and architects
  • Technical leads planning AI adoption
  • Researchers studying autonomous systems

Prerequisites

  • Python programming
  • AI Agents or equivalent experience building with LLM APIs

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 Agentic AI.

Career Relevance

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

  • Agentic AI Engineer
  • AI Solutions Architect
  • AI Engineer
  • Applied AI Researcher

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

Is Agentic AI suitable for beginners?

No. It is an advanced course. Beginners should start with Artificial Intelligence, Generative AI or Prompt Engineering, then take LLM Applications and AI Agents.

Does the course include research exposure?

Agentic AI is an active research area, and the course discusses current papers and open problems. Learners interested in going further can explore AIIT Roorkee's research mentorship programs.

Will I deploy an agentic system?

You build and run agentic workflows in a controlled environment, including monitoring and evaluation, and prepare a plan for how the system would be deployed responsibly.

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

Agentic AI Developer Console

Start Learning Agentic AI

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

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