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Cisco AI Technical Practitioner Advanced (AITECHA)

Length 2 days
Version 1.0

Course overview

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Why study this course

The Cisco AI Technical Practitioner Advanced (AITECHA) training course is an expert-level continuation of the Cisco AI Technical Practitioner (AITECH) Learning Path, designed for practitioners building production-grade agentic AI systems. The living domain-driven design structure ensures the curriculum evolves as the technology landscape changes. Through this training, you’ll gain an understanding of the full engineering stack for production agentic AI systems. You will start by building a working agent from the ground up, learn to structure its outputs for reliable downstream integration, connect it to external tools via the Model Context Protocol (MCP), instrument and monitor it in production, give it memory and retrieval capabilities, and finally harden it against the security threats that come with autonomous tool use. Each course builds on the last—by the end you have the skills to design, deploy, and operate agents that are production-ready, not just demo-ready.

This training also earns you 21 Continuing Education (CE) credits toward recertification.

Cisco Learning Credits: Use your Cisco Learning Credits (CLC's) for training and certification with Lumify and let's work together to increase your skills and capabilities. Nominate Lumify as your TRUSTED LEARNING PARTNER through your Cisco Team Captain to allow Lumify to better help you in your Cisco training journey

Exam Vouchers: Cisco exam vouchers are not included in the course fees but can be purchased separately where applicable.

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What you’ll learn

After taking this course, you should be able to:

Construct a functioning AI agent using industry-standard agentic frameworks and debugging practices
Parse and route structured agent outputs to enable reliable downstream system integration
Configure MCP servers and integrate external tools into AI-powered applications
Implement memory, state management, and context retrieval within AI agent systems
Design and build a production multi-agent pipeline in LangGraph using supervisor routing, specialist subgraphs, and parallel execution with structured state handoffs
Monitor and maintain AI agents in production using observability tooling, KPI frameworks, and cost management strategies
Evaluate agentic AI security risks and the technical configuration of Cisco AI Defense, DefenseClaw, and Splunk for threat detection and mitigation

Cisco at Lumify Work

Lumify Work is the largest provider of authorised Cisco training in Australia, offering a wider range of Cisco courses, run more often than any of our competitors. Lumify Work has won awards such as ANZ Learning Partner of the Year (twice!) and APJC Top Quality Learning Partner of the Year.

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Who is the course for?

IT and Network Engineers
Data Analysts
AIOPs Specialists
Solutions Architects
Technical Leads

Course subjects

Build Your First Agent
Structured Outputs and Agent Integration
Equip the Agent: Tools, Skills, and MCP
Memory, State, and Context Management
Multi-Agent Orchestration with LangGraph
Production AI Monitoring and Evaluation
AI Agent Security and Defense

Labs

Build, Extend, and Debug an Agent
Build the Structured Output Pipeline
Extend and Decompose an Agent
Build a Memory- and RAG-Augmented Agent
Build the Multi-Agent Pipeline
Instrument the Multi-Agent Pipeline
AI-Driven Data Exploration

Prerequisites

There are no prerequisites for this training. However, the knowledge and skills you are recommended to have before attending this training are:

Completion of Cisco AI Technical Practitioner (AITECH) Learning Path
Comfortable with Python, REST APIs, and LLM API usage

These skills can be found in the following Cisco Learning Offerings:

Cisco e-Learning

Cisco U. subscriptions and Cisco authorised e-learning courses are now available.

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Cisco Learning Credits Brochure

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.