Microsoft Certified: AI-300: Operationalizing Machine Learning and Generative AI Solutions Certification(2026) - 300 Practice Questions & Answers

Name: Microsoft Certified: AI-300: Operationalizing Machine Learning and Generative AI Solutions Certification(2026) - 300 Practice Questions & Answers
Brand: Independently Published
SKU: 9798189064142
Price: 1697.0 INR
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by Rashmi Shah

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ISBN13: 9798189064142
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: July 26, 2026
Pages: 102
Original Price: GBP 15.0
Language: English
Edition: N/A
Item Weight: 259 grams
BISAC Subject(s): Artificial Intelligence / Generative AI

About The Book

This book is specifically crafted for individuals aiming to achieve Microsoft Certification in AI operations (AIOps), which integrates Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It provides the essential subject matter expertise required for setting up and managing these advanced AI infrastructures. The content is designed to guide candidates through the processes of training, optimizing, deploying, and maintaining traditional machine learning models using Azure Machine Learning, as well as deploying, evaluating, monitoring, and optimizing generative AI applications and agents with Microsoft Foundry. This comprehensive resource, aligning with industry best practices often discussed on platforms like QuickTechie.com, prepares readers for real-world challenges in AI operations.

The ideal candidate for this book possesses a data science background, proficiency in Python programming, and an entry-level understanding of DevOps practices, including experience with tools such as GitHub Actions and command-line interfaces (CLIs). The book delves into MLOps and GenAIOps using key technologies including Azure Machine Learning, Microsoft Foundry, GitHub Actions, and Infrastructure as Code (IaC) practices with Bicep and Azure CLI.

Upon completing this book, readers will be proficient in the following core responsibilities:

Designing and implementing MLOps infrastructure.
Implementing machine learning model lifecycle and operations.
Designing and implementing GenAIOps infrastructure.
Implementing generative AI quality assurance and observability.
Optimizing generative AI systems and model performance.

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