PROJECT 01
Research assistant that uses approved search tools
Example hands-on exercise
AGENTIC AI
Agentic AI.
Understand AI agents, tool use, orchestration, and workflows that carry out multi-step tasks.
AI AgentsTool UseWorkflows
Bangalore, Karnataka, India · Request fees, duration & batch timings
01 / LEARNCore concepts
Understand the foundations
02 / PRACTICEApplied exercises
Work with practical examples
03 / BUILDProject ideas
Explore hands-on workflows
PROGRAM OVERVIEW
What you could learn.
A suggested progression of topics for Agentic AI. The final lesson plan can be confirmed with the institute before enrollment.
01Agent fundamentals and reasoning workflows
02Tool calling and safe tool permissions
03Planning, state, memory, and orchestration
04Multi-step tasks and human approval checkpoints
05Tracing, testing, and evaluating agents
06Security and reliability considerations
Recommended starting point
Python programming and introductory LLM concepts recommended.
PRACTICAL LEARNING
Learning outcomes.
Explore the capabilities this course aims to develop.
Build an agent that calls trusted tools
Design observable multi-step agent workflows
Recognize key failure modes and safe deployment patterns
PORTFOLIO PRACTICE
Project ideas.
Examples of practice projects that could support the learning journey.
PROJECT 02
Multi-step task assistant with human confirmation
Example hands-on exercise
LET'S CONNECT
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