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Enhancing Network Automation with Generative AI

Nick Russo

Generative AI has many new capabilities, but few engineers have integrated those features into existing network automation solutions. This course will teach you how to do exactly that using a realistic use-case.

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Generative AI has many new capabilities, but few engineers have integrated those features into existing network automation solutions. This course will teach you how to do exactly that using a realistic use-case.

This course cuts through today's hype surrounding generative AI by tying the output from the large language models (LLMs) into a complex network automation workflow. In this course, Enhancing Network Automation with Generative AI, you’ll learn to make intelligent requests of your generative AI model, then receive precise and accurate answers. First, you'll discover how to ask generative AI to convert network device configurations across vendors. Next, you’ll explore the power of post-AI/pre-deployment validation by combining off-line tools like pytest and batfish to catch obvious mistakes made by generative AI before deployment. Finally, you'll learn how to programmatically deploy network topologies and subsequently test them using an innovative combination of Python, GNS3, scrapli, textFSM, and asyncio. When you’re finished with this course, you’ll have the skills and knowledge of automation-oriented generative AI needed to solve specific business problems relating to network configuration, troubleshooting, deployment, and validation.

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What's inside

Syllabus

Course Overview
Using GPT to Convert Network Configurations
Optimizing AI with Fine-tuning and Embeddings
Reviewing Network Configurations with Batfish and Pytest
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Building On-demand Test Topologies with GNS3
Parsing Structured Data from CLI Outputs with TextFSM
Validating Test Topologies with Scrapli and Asyncio

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Deepens understanding of network configuration and automation using generative AI
Explores specific business problems and their solutions in the realm of network configuration, troubleshooting, deployment, and validation
Introduces the use of machine learning models to optimize network automation
Emphasizes hands-on practice through the inclusion of innovative combinations of Python libraries and tools for network automation
Implements realistic use-cases to demonstrate the applications of generative AI in network automation
Taught by Nick Russo, an experienced instructor in the field of network automation and generative AI

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Career center

Learners who complete Enhancing Network Automation with Generative AI will develop knowledge and skills that may be useful to these careers:
Automation Architect
An Automation Architect specializes in the design and maintenance of automated systems for network infrastructure. This course will augment your skills in network automation by bolstering your knowledge of Generative AI, a revolutionary technique for automating software tasks including network configuration, troubleshooting, deployment, and validation. The material covered will help you accelerate projects and minimize errors, solidifying your expertise in optimizing automation for the modern network.
Network Architect
A Network Architect designs, builds, and maintains network infrastructure for various organizations. This course on Enhancing Network Automation with Generative AI will provide you with the skills to automate network tasks, freeing up your time to focus on higher-level architectural concerns. You'll learn how to convert network configurations across vendors, optimize AI with fine-tuning and embeddings, and validate test topologies with Scrapli and Asyncio.
Network Engineer
Network Engineers install, configure, and maintain computer networks for businesses and organizations. This course on Enhancing Network Automation with Generative AI will introduce you to cutting-edge techniques for automating network tasks, a skill that is increasingly in demand as companies move to more complex and dynamic network environments. You'll gain hands-on experience with tools and techniques for automating network configuration, troubleshooting, deployment, and validation.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course on Enhancing Network Automation with Generative AI will provide you with the skills and knowledge to build intelligent network automation solutions using Generative AI. You'll learn how to use large language models (LLMs) to make intelligent requests and receive precise and accurate answers. This hands-on training will help you develop in-demand skills that can accelerate your career as a Software Engineer.
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations teams. This course on Enhancing Network Automation with Generative AI will provide you with the skills and knowledge to automate network tasks, a critical aspect of DevOps. You'll learn how to use Generative AI to convert network configurations across vendors, optimize AI with fine-tuning and embeddings, and validate test topologies with Scrapli and Asyncio. This training will help you become a more effective DevOps Engineer and contribute to the success of your organization's software development lifecycle.
Network Administrator
Network Administrators manage and maintain computer networks for businesses and organizations. This course on Enhancing Network Automation with Generative AI will provide you with the skills and knowledge to automate network tasks, a critical aspect of network administration. You'll learn how to use Generative AI to convert network configurations across vendors, optimize AI with fine-tuning and embeddings, and validate test topologies with Scrapli and Asyncio. This training will help you become a more efficient and effective Network Administrator.
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to network automation tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to network automation tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Cloud Engineer
Cloud Engineers design, build, and maintain cloud computing systems. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to cloud networking tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Network Security Engineer
Network Security Engineers design, implement, and maintain security measures for computer networks. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to network security tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Systems Administrator
Systems Administrators manage and maintain computer systems, including servers, desktops, and networks. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to systems administration tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
IT Manager
IT Managers plan, direct, and coordinate the activities of an organization's IT department. This course on Enhancing Network Automation with Generative AI may be useful for those interested in gaining a better understanding of how Generative AI can be used to improve network automation. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Software Developer
Software Developers design, develop, and maintain software applications. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to software development tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to data engineering tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.
Database Administrator
Database Administrators manage and maintain databases. This course on Enhancing Network Automation with Generative AI may be useful for those interested in applying Generative AI techniques to database administration tasks. The course covers topics such as using GPT to convert network configurations, optimizing AI with fine-tuning and embeddings, and reviewing network configurations with Batfish and Pytest.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Enhancing Network Automation with Generative AI.
Explores the theoretical foundations of generative AI and provides practical guidance on building and deploying generative AI models.
Provides a comprehensive introduction to the mathematical foundations of machine learning, covering topics such as linear algebra, calculus, and probability theory.
This widely used book offers a clear and accessible introduction to deep learning. It serves as a valuable reference for those seeking to enhance their understanding of the fundamentals.
Provides a practical guide to using Scikit-Learn, Keras, and TensorFlow for machine learning tasks, covering topics such as data preprocessing, model training, and model evaluation.
Provides a comprehensive introduction to network automation using Python, covering topics such as network programmability, configuration management, and monitoring.
Provides a practical guide to using PyTorch for natural language processing tasks, this book covers topics such as text classification, sentiment analysis, and machine translation.

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