Descriptions
AI for Network Engineering: Building Intelligent NetDevOps, Take your network automation skills into the AI era with AI for Network Engineering: Building Intelligent NetDevOps. This advanced course introduces the next major shift in network operations: moving beyond brittle scripts and reactive troubleshooting toward intelligent systems that can reason, predict, validate, and act. You will learn how to combine proven NetDevOps principles with modern artificial intelligence, including machine learning, predictive analytics, and large language models. You will explore how AI can enhance traditional network automation workflows by helping engineers detect anomalies, validate complex configuration changes, troubleshoot faster, query the network through ChatOps, and generate useful operational documentation. You will review the limits of traditional automation and learn practical architectural patterns for integrating AI into NetDevOps pipelines using tools such as Ansible, Terraform, Git-based workflows, and network source-of-truth platforms, alongside frameworks and libraries such as Scikit-learn, PyTorch, LangChain, and Hugging Face. Through real-world examples, you will see how intelligent automation can reduce operational overhead, improve network resiliency, and support proactive decision-making.
The course examines four key use cases for AI-enhanced network operations: intelligent configuration validation, AI-assisted troubleshooting, ChatOps for network teams, and automated documentation with a RAG-based knowledge base. You will also learn best practices for building trustworthy AI-driven systems, including managing data quality, reducing model risk, addressing hallucinations, securing AI workflows, and determining when AI is or is not the right tool. By the end, you will understand how to design and build next-generation automation solutions that learn from data, reason through complex conditions, and help engineers manage increasingly complex infrastructure. The course is intended for network engineers, automation specialists, architects, and infrastructure professionals who want to move from traditional automation toward intelligent, self-adapting networks. All Jupyter notebooks used throughout the course are available in the companion GitHub repository, allowing you to run the demonstrations in your own environment.
What you’ll learn
- Apply AI and machine learning concepts to real-world network automation challenges.
- Design intelligent NetDevOps pipelines that combine automation tools with AI frameworks.
- Use AI to improve configuration validation, troubleshooting, optimization, and documentation.
- Integrate tools such as Ansible, Terraform, GitLab, NetBox, Scikit-learn, PyTorch, LangChain, and Hugging Face.
- Build AI-augmented workflows that reduce operational overhead and improve network resiliency.
- Recognize the risks, limitations, and best practices of using AI in network operations.
Who this course is for
- Practicing network engineers who want to evolve from traditional automation to intelligent, AI-driven network operations.
- Network architects seeking to design intelligent and resilient network automation systems.
- DevOps engineers and Site Reliability Engineers interested in applying AI to network operations and automation workflows.
- Infrastructure automation developers who want to integrate AI frameworks and tools into NetDevOps pipelines.
- Technical leaders working with enterprise networks, service provider environments, cloud infrastructure, or large-scale automation systems.
- Professionals with networking fundamentals and scripting experience, such as Python, who want to advance their knowledge of AI-enhanced NetDevOps.
Specificatoin of AI for Network Engineering: Building Intelligent NetDevOps
- Publisher : Oreilly
- Teacher : Marco Morales
- Language : English
- Level : All Levels
- Duration : 4 hours and 23 minutes
Content of AI for Network Engineering: Building Intelligent NetDevOps
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720p
Download Links
Password file(s): www.downloadly.ir
File size
2.3 GB