The Designing, Deploying and Managing Network Automation Systems (AUTOCOR) Learning Path prepares you for a professional role as a network automation engineer. It focuses on designing and implementing automation systems, from writing Python scripts and Ansible playbooks, and applying Terraform for network automation, to building complex CI/CD pipelines that integrate multiple tools. The Learning Path also shows how to leverage AI for network automation by building Large Language Model (LLM)-powered network agents and by using MCP servers. Additionally, the Learning Path focuses on operational aspects of managing a modern, automated network and explores secure coding practices, collecting logs, containerization, and model-driven telemetry. Overall, the Learning Path focuses on practical implementation that directly prepares you to design, deploy, and operate automated networks.

This Learning Path prepares you for the 350-901 AUTOCOR v2.0 exam. If passed, you earn the Cisco Certified Specialist - Automation Core certification and satisfy the core exam requirement for the Cisco Certified Network Professional (CCNP) Automation and Cisco Certified Internetwork Expert (CCIE) Automation certifications.

Skills You'll Learn:

• Implement useful tools such as Python, Ansible, and Terraform for network automation
• Manage Network as Code and set up advanced CI pipelines using tools such as GitLab CI, CML, and PyATS
• Manage the operational aspects of modern, fully automated networks
• Use AI to push automation solutions even further

Learning Path Objectives:

• Network Automation: Build a strong foundation in automating network devices through hands-on courses that progress from CLI scripting to REST APIs, RESTCONF, and advanced tools like Ansible and Terraform.
• Infrastructure as Code: Adopt the Network as Code approach by progressing from basic automation with Python, Ansible, and Terraform to advanced practices like state tracking with Git, CI pipeline deployment, CML test environments, and automated testing with pyATS.
• Operations and Security in Automated Networks: Enhance operational network automation by configuring model-driven telemetry, collecting logs, applying secure coding, containerizing solutions, and deploying trusted TLS certificates.
• AI for Network Automation: Leverage artificial intelligence and large language models to enhance network automation by generating code, deploying private conversational agents, integrating with MCP servers for live data collection, and applying these tools to real-world automation tasks.

Designing, Deploying and Managing Network Automation Systems E-Learning