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Microsoft Course: Operationalize generative AI applications (GenAIOps)

GenAIOps Mastery: Scaling Generative AI with Precision
  • Deploy scalable AI solutions​​
  • ​​Optimize model selection
  • ​​Implement robust evaluations
  • ​​Mitigate operational risks
  • ​​Leverage GenAIOps tools​​
  • Build a base for specialized roles in AI development or cloud engineering
  • Prepare for more advanced Microsoft certifications in AI

What you will learn

"Operationalize Generative AI Applications (GenAIOps)" is a ​​1-hour 28-minute course​​ designed for developers and AI practitioners aiming to deploy and scale generative AI solutions effectively. Focused on ​​GenAIOps​​ (Generative AI Operations), the curriculum covers strategic planning, model lifecycle management, and performance evaluation of AI applications. Learners will explore code-first development approaches, compare language models (e.g., GPT-4, Claude), and implement custom evaluators to measure AI outputs against business goals. The course emphasizes reproducibility and reliability, aligning with industry practices for integrating generative AI into enterprise workflows.

​​Microsoft's Operationalize generative AI applications (GenAIOps) course Outline

Learn the Operationalize generative AI applications (GenAIOps)

This ​​1.5-hour course​​ teaches you to operationalize AI applications with enterprise-grade reliability. Learn to evaluate model performance, automate workflows, and align AI outputs with business KPIs. Backed by Microsoft's expertise, it's ideal for teams preparing for AI certification exams. Enroll now and turn experimental AI into measurable ROI! ? "90% of enterprises report improved AI reliability after adopting GenAIOps practices."

Start your journey today:

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Course Structure Includes:

Module 1​​: GenAIOps Foundations (50 min)

  • Use case analysis (e.g., chatbots, document automation).
  • Model selection strategies (comparing OpenAI, Azure AI, and open-source LLMs).
  • Tools like LangChain and Semantic Kernel for reproducible workflows.

Module 2​​: Evaluation & Optimization (38 min)

  • Metrics design (accuracy, bias, latency).
  • Custom prompt-based evaluators for domain-specific tasks.
  • Interpreting results to avoid overfitting and data leakage.
 

Training Options

Self Paced Learning
  • Lifelong access to high-quality content
  • Curated by industry experts
  • Customized learning progress
  • 24/7 learner assistance and support
  • Follow the latest technology trends
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Exam Dump
  • 100% Real Exam Practice Tests
  • 100% Verified Exam Questions & Answers
  • 100% Guarantee Passing Rate
  • Average 7 Days to Practice & Pass
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Description

Learn to deploy, evaluate, and optimize generative AI applications using GenAIOps frameworks. Master model selection, metrics, and ethical compliance.

Pre-requisites

You should be familiar with fundamental generative AI concepts and services in Azure.

SPOTO Empowers You to Earn Your Certification.

Benefits of AWS Certified AI Practitioner Certification

​​Microsoft Certified: Azure AI Fundamentals (AI-900)​​ is an entry-level certification designed to validate foundational knowledge of AI and machine learning concepts, including computer vision, natural language processing (NLP), generative AI, and responsible AI principles. Ideal for both technical and non-technical professionals, it requires no prior coding experience and offers free, flexible learning resources via Microsoft Learn. The certification enhances career prospects in high-demand roles like AI Engineer or Data Scientist, with potential salary increases up to 20%, while serving as a gateway to advanced Azure certifications (e.g., AI-102). Cost-effective and time-efficient (preparation in 10–30 hours), the exam focuses on real-world applications using Azure Cognitive Services, OpenAI APIs, and Azure Machine Learning. With permanent validity and global recognition across 90+ countries, it equips professionals to drive AI innovation in industries such as healthcare and finance. Start your AI journey with Microsoft Learn today!

Advantages of Using SPOTO's Exam Preparation Materials

SPOTO's study resources provide comprehensive coverage of the exam syllabus, aligning with key topics like ML problem framing, data processing, model optimization, and pipeline automation. The materials include structured learning paths, practice exams, and real-world case studies that mirror the certification's focus on designing, implementing, and deploying machine learning solutions with Microsoft services and ML workflows. By leveraging SPOTO's targeted content, candidates can efficiently bridge knowledge gaps, reinforce practical skills, and gain familiarity with the exam format. This focused preparation increases confidence and readiness, particularly for complex tasks such as deploying CI/CD pipelines or optimizing model performance—areas emphasized in the certification. Combined with hands-on experience, SPOTO's resources offer a strategic advantage for achieving certification success.

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