Whizlabs

Generative AI for Azure Cloud Engineers

Whizlabs

Generative AI for Azure Cloud Engineers

访问权限由 Coursera Learning Team 提供

深入了解一个主题并学习基础知识。
中级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
中级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

要了解的详细信息

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作业

12 项作业

授课语言:英语(English)
最近已更新!

March 2026

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有4个模块

In Week 1, you’ll be introduced to the fundamentals of Generative AI. You’ll learn what Generative AI is, its key components, and how it enables intelligent applications across various industries. The week covers Generative AI architecture, common enterprise scenarios, and Responsible AI considerations. By the end of this week, you’ll understand how Generative AI works and its role in modern cloud engineering and enterprise solutions.

涵盖的内容

5个视频2篇阅读材料2个作业1个讨论话题

Week 2 focuses on Azure OpenAI Service and its capabilities for building AI-powered applications. You’ll explore natural language processing, code generation, image generation, and prompt engineering techniques. You’ll also learn how to use REST APIs, configure model parameters, use multimodal models, and fine-tune models to meet specific business requirements. By the end of this week, you’ll be able to use Azure OpenAI Service to build and integrate Generative AI solutions into Azure cloud applications.

涵盖的内容

13个视频1篇阅读材料3个作业

In Week 3, you’ll explore Microsoft Copilot and Copilot Studio capabilities. You’ll learn how Copilot enhances productivity across Microsoft services and enterprise environments. You’ll also learn how to create conversational agents, build intelligent bots using Copilot Studio, and integrate Generative AI into business applications using Microsoft Power Platform. By the end of this week, you’ll understand how Copilot and Copilot Studio enable intelligent automation and enterprise AI integration.

涵盖的内容

10个视频1篇阅读材料3个作业

In Week 4, you’ll focus on operational and monitoring aspects of Azure data solutions. You’ll learn how to monitor data platforms using Azure Monitor, track and manage pipelines in Azure Data Factory, and handle ingestion scenarios using Azure Event Hubs and Azure Data Explorer. You’ll also explore Azure Databricks and foundational big data concepts such as HBase on HDInsight. By the end of this week, you’ll be able to monitor, troubleshoot, and manage Azure-based data pipelines and analytics solutions effectively.

涵盖的内容

12个视频3篇阅读材料4个作业

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