DevOps and GenAI using .NET, Azure OpenAI and GitHub

Packt via Coursera

Go to class Write review

Details

Go to class

Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

7 weeks, 1 hour a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

Unlock All Certificates

This course explores the integration of Generative AI into modern DevOps workflows. It covers AI-assisted automation, pipelines, and agentic systems. Learners gain practical skills using .NET, Azure OpenAI, and GitHub. This course begins by establishing a strong foundation in Generative AI within the DevOps ecosystem, explaining how AI enhances efficiency, decision-making, and automation across the software delivery lifecycle. Learners explore key concepts such as AI-assisted versus autonomous DevOps, along with critical risk considerations including hallucinations, model drift, and operational reliability. The course then transitions into practical implementation, where learners apply AI to real DevOps scenarios such as infrastructure as code, pipeline generation, testing strategies, release automation, and incident response. Through guided demonstrations, learners gain hands-on experience integrating AI into workflows using tools like .NET, Azure OpenAI, and GitHub, improving speed, consistency, and delivery outcomes. In the final phase, advanced topics such as enterprise governance, secure integration patterns, and agentic AI systems are explored in depth. Learners design intelligent pipelines, orchestrate AI-driven workflows, and implement autonomous agents with observability and control, enabling scalable, secure, and production-ready DevOps practices aligned with modern enterprise needs. This course is ideal for DevOps professionals, engineers, and IT managers looking to leverage AI to optimize their workflows. A basic understanding of DevOps concepts and tools such as GitHub and cloud services is recommended for participants. The course combines theory with hands-on demonstrations using real-world tools. You'll progress from basic AI concepts to advanced topics like AI agents in DevOps workflows. The practical approach ensures you can immediately apply your knowledge. This course is based on DevOps and GenAI using .NET, Azure OpenAI and GitHub, by Trevoir Williams. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

Introduction
- This module provides an overview of the course structure, objectives, and the tools used in DevOps and GenAI. Learners will gain clarity on how the course is organized and the integration of key technologies in a modern development environment.
Generative AI Concepts for DevOps
- This module explores how generative AI enhances DevOps workflows, covering its applications throughout the development lifecycle, risks involved, and strategies for safe integration. Learners will gain insights into AI-driven efficiency, decision-making, and risk mitigation in real-world DevOps scenarios.
Practical AI-Assisted DevOps
- This module explores how AI enhances DevOps workflows by improving infrastructure management, CI/CD pipeline efficiency, test strategies, and release documentation. Learners will gain practical insights into AI-driven tools and their real-world applications in DevOps practices.
DevOps AI Tools, Governance, and Enterprise Readiness
- This module explores the integration of AI tools into DevOps practices, focusing on governance, enterprise readiness, and responsible AI adoption. Learners will gain insights into selecting and implementing AI solutions while ensuring compliance, accountability, and operational effectiveness.
Integrating Generative AI into DevOps Pipelines
- This module provides learners with the knowledge and skills to integrate generative AI into DevOps pipelines. It covers key aspects such as provisioning AI engines, designing deterministic workflows, orchestrating tasks in GitHub Actions, and implementing secure and efficient AI-assisted processes. Learners will also explore observability, cost management, and context engineering for improved AI performance.
Agentic AI for Advanced DevOps Scenarios
- This module explores the integration of agentic AI in DevOps workflows, covering the design, implementation, and evaluation of intelligent agents. Learners will gain hands-on experience with building and testing AI agents in CI/CD pipelines, GitHub workflows, and multi-agent systems. The module also emphasizes best practices for memory management, interoperability, and observability in AI-driven DevOps environments.
Conclusion
- This module reviews the key concepts from the course and provides practical recommendations for implementing DevOps and GenAI in real-world situations. Learners will gain insights into how to apply these technologies effectively and efficiently.