Azure Cloud Computing
Overview
- Introduction to cloud computing and Azure
- Setting up and managing Azure resources (storage, compute, networking)
- Working with virtual machines (VMs) and containers
- Deploying and managing applications on Azure
- Implementing security best practices in the cloud
- Monitoring, troubleshooting, and optimizing Azure resources
- Introduction to Azure AI and machine learning services
- Using Azure DevOps for continuous integration/continuous delivery (CI/CD)
What You’ll Learn
In this course, you’ll be introduced to Microsoft Azure, one of the leading cloud platforms used by businesses worldwide. You’ll learn the fundamental concepts of cloud computing, as well as how to navigate and utilize Azure services to build, deploy, and manage applications and resources. Key topics covered include:
By the end of the course, you’ll be capable of working with core Azure services, managing cloud-based solutions, and understanding how to integrate Azure tools into a business’s infrastructure.
Job Opportunities: Azure Cloud Computing is in high demand across industries. After completing this course, you’ll be equipped for several key roles in the cloud computing and IT industry, including:
- Cloud Architect
- Azure Solutions Architect
- Cloud Administrator
- Azure Developer
- DevOps Engineer
- Systems Engineer
- Cloud Security Specialist
- IT Support Specialist
- Cloud Consultant
As businesses increasingly move to the cloud, there is a growing need for skilled professionals who can manage, optimize, and secure cloud infrastructures, especially on platforms like Azure.
Chapters
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Introduction to Cloud Computing and Azure
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Azure Fundamentals
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Virtual Machines and Storage
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Networking in Azure
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Azure Security Essentials
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Azure App Services and Deployment
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Monitoring and Troubleshooting Azure
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Azure AI and Machine Learning Overview
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Introduction to DevOps in Azure
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Mini Project
Students are required to complete 39 hours of in-class training.
39 hours
Program Summary
This table will display a summary of total instructional hours, delivery format and percentage weight for every Type of Learning entered in the List of Subjects. The ministry, career college and any subject or education assessors may refer to this section for a general understanding of the components of the program.
| Type of Learning | Total Instruction Hours | Delivery Format | % Weight |
|---|---|---|---|
| Theory | 20.00 | On-Line | 58.67% |
| Practical | 19.00 | On-Line | 41.33% |
| Total Type of Learning | 39.00 | ||
| Total Program Hours | 39.00 | 100.00% |
$CAD
Details
Certification
39 Hours
Updated: 03/01/2025
Prerequisites
If you attended a post-secondary institution after high school, we need both your high school transcript and your post-secondary transcript.
- Entry into many of our programs is competitive and your post-secondary marks can strengthen your application.
- If you did not graduate from high school and have a GED, send us a copy.
- Even if you graduated a while ago, we still need your high school transcript.
- If you cannot obtain it, let us know and we can discuss your options.
- If you studied at college or university, you must submit your post-secondary transcript AND
your high-school transcript. This may strengthen your application.
- Basic understanding of machine learning concepts.
- Familiarity with Python programming and libraries like TensorFlow or PyTorch.
- Understanding of neural networks and deep learning fundamentals.
Get In Touch or Create an Account
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