AZURE AI Services
During the time period from January 29 to February 2, 2024, I had the privilege of experiencing a hands-on session on Microsoft’s Azure AI services. In this blog, let me share some insights about Azure and its services.
How I got Azure access:
Saveetha Engineering College, in association with ICT Academy, was generous enough to organize “Student Certification Programs”.
During this program, students had the opportunity to receive training from various talented corporate trainers through actual hands-on sessions on different platforms. We were given the option to choose from three courses:
- Microsoft Azure AI Engineer Associate program
- Cloud Practitioner (AWS)
- Robotic Process Automation - UI Path
I opted for the Microsoft Azure AI Engineer Associate program.
Training:
A batch of 50 students was assigned to Mr. Syed Irfan Ali, a certified Azure Administrator Associate and Cybersecurity Instructor. Below are the insights he provided, along with the self-learning I acquired during this 5-day session.
What is Azure?
Azure is a versatile cloud computing platform run by Microsoft. It offers easy access, management of resources, and the development of applications and services through global data centers.
“A data center is a dedicated space within a building or a group of buildings used to house computer systems and servers. It serves for the remote storage, processing, or distribution of large amounts of data that can be utilized by various organizations.”
Microsoft Azure currently operates in 62 regions, with an additional 18 under development. This expansion will bring the total to 80 regions in the near term.
Within each Azure region, there are 1 to 3 unique physical locations, known as availability zones, resulting in over 200 physical data centers located in various global locations.
The presence of availability zones is crucial to safeguard data and applications from potential data center failures. This ensures that even if one zone encounters an issue, there are backup zones available to maintain the reliability and continuity of services.
To have a virtual and fun learning experience about Microsoft’s data centers, check out the links below.
3D Globe — — — — Take a virtual tour to Microsoft’s Datacenter
Azure Services:
Azure Cloud integrates all of Azure’s services, such as Compute Services, Data and Analytics Services, Networking Services, Storage Services, AI and Machine Learning Services, Identity and Security Services through various REST APIs and SDK.
“An API, or Application Programming Interface, serves as a set of defined rules that enable different software applications to communicate and interact with each other.”
As part of the program, we had the opportunity to explore Azure’s AI services.
Why Azure AI Services:
When it comes to AI and ML models, obtaining the right dataset and selecting the best algorithm for the data can be a challenging task. Azure makes this process easy and significantly improves speed-to-market.
“Azure AI Services are a portfolio of AI services that can be incorporated into applications quickly and easily without specialist knowledge.”
Azure AI services are based on three principles:
- Prebuilt and ready to use — Azure provides prebuilt source codes in both C# and Python for higher adaptability and ease. It also comes with pre-fed refined datasets and pre-trained machine learning models, contributing to higher accuracy and enhancing the overall quality of the product.
- Accessed through APIs — Azure AI services are designed to be used in different development environments, with minimal coding. APIs enable software components to communicate, so one side can be updated without stopping the other from working.
- Available on Azure — As these services are accessed through the Azure cloud, it ensures the availability of resources, supports a pay-per-use model, and satisfies the on-demand provisioning of resources.
Lab Sessions:
We had a total of 13 lab sessions that navigated from image recognition to advanced data extraction. The first lab explained how to use Azure AI services, whereas the rest covered the following concepts.
For each lab, the instructions were self-explanatory, and every step was explained clearly. Learners were given accessibility to choose their preferred programming languages such as Python or C#.
Resource Groups:
All the labs were conducted in a virtual environment using Azure Cloud. To utilize Azure services, you need to have a subscription (payment made to access and use the services) and create a resource group to make use of them.
Your development requirements and how you want costs to be billed determine the types of resources you need.
- Multi-service resource: Provides access to multiple Azure AI services with a single key and endpoint. When you use an Azure AI services resource, all your AI services are billed together.
- Single-service resources: Provides access to a single Azure AI service, such as Speech, Vision, Language, etc. Each Azure AI service has a unique key and endpoint. These resources might be used when you only require one AI service or want to see cost information separately.
Interface:
When starting a lab, a virtual machine with the interface shown below will open. You’ll notice an instruction page in the corner of the screen. Simply complete the tasks outlined in the instructions to successfully complete the lab.
Always remember not to use your own credentials anywhere. You can find alternate credentials in the resource section on top of the instruction column. You can use the proxy credentials to log in to Azure portal.
The Azure portal essentially encompasses all services. To access Azure AI services, you navigate within the portal.
In the left-side column, you can find various AI services provided by Azure. Throughout this lab, we will utilize these services to accomplish our tasks. By the end of the session, we will also become familiar with creating a multiservice resource group.
Pre-requisite:
To complete the labs successfully, you need basic knowledge of:
- Commands in VS Code, such as git clone
- Navigating files in VS Code
- VS Code terminal usage
- Python/C# knowledge
- Understanding the tasks
Reflections on Azure:
Working in the Azure platform has highlighted the efficiency gained when deploying models with well-prepared datasets already trained by experts. The ease of use and the extensive range of available services truly revolutionize the AI and ML domain.
I am genuinely grateful to ICT Academy and Saveetha Engineering College for organizing this session.
Hats off to Mr. Syed Irfan Ali for his training in Azure platforms, patiently addressing every doubt. Your professional yet soft-spoken demeanor made it comfortable for all of us to share our thoughts and inquiries. Thank you!
To the readers:
While I’d love to delve into the details of each lab and its insights, the true value lies in experiencing them firsthand. After all, these sessions are hands-on, offering a richer understanding when explored independently. If you are someone genuinely interested in Azure AI platforms, I trust this blog has provided a foundational understanding of what Azure is and its extensive applications. Your opinions are always welcomed!
Wanna learn more? — continue……