CCNA Automation (200-901 CCNAAUTO) v1.1

For IT leaders: Many network teams still make changes by hand at the CLI, one device at a time. That approach slows rollouts and raises the risk of configuration errors reaching production. This course gives network engineers a structured path from manual configuration work to version-controlled, API-driven automation across Cisco IOS-XE, Nexus, ACI, Catalyst Center, SD-WAN, Meraki, and security platforms.

Role fit: This course suits network engineers and administrators who already know networking fundamentals and now need code and automation skills. A network fundamentals section is included for practitioners who need a refresher.

Time investment: Plan for about 32.5 hours across 34 skills per learner, plus time for hands-on practice.

Change-management notes:

• Set expectations early. The trainer warns that learning Python can feel like starting over for experienced network engineers. Budget extra time for the Git and Python skills, which come first in the course.
• The course stresses testing automation in a simulated lab before pushing changes to production. Teams can carry that practice into their own change control.
• Some Cisco platform skills focus on API capabilities, documentation, and how the services work rather than writing code against every live environment. Use those sections to build API awareness before mapping lab access and change controls to the platforms your team manages.

How CBT Nuggets supports the outcome: The course is delivered as an ordered Playlist. Challenge sections throughout let learners check their skills before moving on.

IT teams complete this training to move network changes out of one-off CLI sessions and into tested, version-controlled automation. The course builds on networking experience your team already has. It adds Git, Python, and Cisco APIs, then applies them across IOS-XE, Nexus, ACI, Catalyst Center, SD-WAN, and Firepower.

• Safer changes through lab-first testing: Your team learns to build a virtual lab that mirrors production and to test automation scripts and Ansible playbooks there before rollout. The course also flags real risks, such as lab OSPF neighbors leaking fake routes into the physical network.
• Faster incident response through integration: In the SD-WAN challenge, learners write a script that pulls and parses alarms. They then plan webhook-style integrations that route those alarms to email or paging tools, so the right people learn about active issues sooner.
• Shared, auditable workflows: Engineers practice Git branching and merging, plus GitHub issues and pull requests. This gives every change a commit history and a clear review path. The course also shows gists as a lightweight way to keep versioned recovery runbooks.
• Scalable configuration management: Your team works with YANG and NETCONF, RESTCONF, NX-API, and Ansible to push consistent changes across many devices. Learners also get an introduction to NSO and Terraform for broader orchestration.

The course starts with basic software development skills, then moves into Cisco network automation. That progression helps engineers read, understand, and review scripts before those workflows touch production environments.

Knowledge

• How Git branching, merging, and GitHub collaboration features — including pull requests, issues, and gists — support team-based source control for automation code
• Python fundamentals for network automation: data types, control flow, functions, classes, and data serialization with JSON, XML, and YAML
• How YANG data models work with NETCONF, and how RESTCONF and NX-API expose IOS-XE and Nexus devices to programmatic control
• The role of APIs and SDKs across Cisco platforms, including ACI, Catalyst Center, SD-WAN, Meraki, Firewall Management Center, ISE, Webex, and compute and collaboration APIs
• Where infrastructure as code concepts fit alongside DevOps principles, the SDLC, CI/CD, OWASP threats, and application testing
• The networking fundamentals that automation affects: IP subnetting, MAC and IP addressing, network architecture, components, and services

Ability

• Create feature and bug-fix branches, then commit, merge, and collaborate on automation code through GitHub
• Write Python scripts that call REST APIs, parse structured responses, and work with JSON, XML, and YAML data
• Build a virtual network automation lab that stays isolated from production, so test scripts can safely break and validate automation workflows
• Retrieve and parse operational data, such as device inventory, and prepare API workflows for further automation
• Use Cisco API documentation, Postman, Python, and platform SDKs to interact with Cisco automation endpoints
• Use lab and modeling tools to practice network automation workflows in simulated environments before applying them to production systems