Cary, NC, Nov. 18, 2025 (GLOBE NEWSWIRE) — INE, a global leader in network and IT training, today announced the release of its newest networking course, AI in Automation, designed to give engineers practical, hands-on experience integrating Artificial Intelligence into network infrastructure automation. The course brings together cutting-edge concepts in AI-driven network management and large language model (LLM) integration, offering students a rare opportunity to experiment directly with intelligent network workflows in a virtual lab environment.
Developed by expert instructor Rohit Pardasani, the course explores how AI in automation can elevate modern infrastructure operations beyond static scripts into systems capable of reasoning, adapting, and learning. Through guided exercises, learners connect a real LLM, Anthropic’s Claude, to routers in a virtual topology using the Model Context Protocol (MCP), observing firsthand how artificial intelligence can analyze, interpret, and respond to live network data.
“Traditional automation stops at execution,” said Pardasani. “With LLM-based systems, we can now build adaptive network systems that understand intent, contextualize commands, and maintain safe, auditable workflows. This course helps engineers take that next leap to create automation that thinks.”
Transforming Network Infrastructure Through AI
INE’s AI in Automation course is part of the company’s broader Automating & Programming Cisco Enterprise Solutions (300-435 ENAUTO) Learning Path, supporting learners preparing for the Cisco ENAUTO (300-435) certification exam. The course bridges theoretical AI principles with practical automation frameworks, enabling students to:
- Build autonomous networking workflows that integrate AI decision-making.
- Safely deploy LLMs within network infrastructure automation environments.
- Use plain-language prompts to generate network insights, such as generating an inventory of software versions, verifying configurations, or identifying anomalies.
- Implement controls ensuring every automated action is logged and reversible.
The result is a realistic simulation of enterprise-grade network automation enhanced by AI, a crucial skill set as organizations pursue agility, resilience, and efficiency in their IT ecosystems.
A Hands-On Approach to the Future of Networking
The course’s lab-centric design underscores INE’s commitment to immersive, experience-driven education. Learners don’t just watch demonstrations; they architect automation pipelines that leverage AI’s interpretive power. By applying LLMs to router automation labs, students see the tangible difference between code that executes commands and code that understands them.
“AI has already redefined industries from content creation to cybersecurity,” said Brian McGahan, Director of Networking Content for INE. “This course shows how those same innovations are reshaping networking and making automation more intelligent, responsive, and strategic.”
INE’s training framework allows learners to test integrating Large Language Models (LLMs) with network infrastructure in a safely controlled, virtualized environment. Participants can test, iterate, and measure AI-driven responses before applying them to production-level systems, ensuring both innovation and security remain central to their automation workflows.
The AI in Automation course is now live on the INE platform. Students can begin learning immediately, access on-demand labs, and progress towards obtaining Cisco’s CCNP Automation Certification, while exploring real-world AI applications.
About INE
INE is an award-winning, premier provider of online networking and cybersecurity education, including cybersecurity training and certification. INE is trusted by Fortune 500 companies and IT professionals around the globe. Leveraging a state-of-the-art hands-on lab platform, advanced technologies, a global video distribution network, and instruction from world-class experts, INE sets the standard for high-impact, career-advancing technical education.
- INE Debuts Hands-On AI Automation Course