Azure Cognitive Services Hands-on Workshop resources and insights.

This post has been republished via RSS; it originally appeared at: New blog articles in Microsoft Tech Community.


The agenda of the workshop was to provide students with a hands-on experience of Microsoft Azure Cognitive Services focusing mainly on Custom Vision and QnA Maker.

Also provided a brief introduction to Microsoft Azure and fundamentals of cloud computing concepts. Help them figure out how to exhibit Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP) projects on their resume.


The workshop was attended by 30 students. All students received a Microsoft Azure for Student subscriptions.


Starting with the basic concepts of cloud computing and how Azure Cognitive Services fits into the Microsoft Azure ecosystem. Elaborating on how API calls embed the ability to see, hear, speak, search, understand, and accelerate advanced decision-making into modern applications.

Quick revision of services under the Cognitive Services umbrella such as:

Flow of the workshop

After the introduction, the subscription were created by the students. Activating Azure for Student provided each of the students with a balance of $100 USD that they could use to explore and experiment with the services on the Azure portal.

All the activities performed were strictly directed by the Learning module on Microsoft Learn

Custom Vision


Click the Custom Vision title to view the Microsoft Learn Document for this activity.

The first activity to be performed was on Custom Vision, where we discussed:

  • What is Custom Vision?

  • What are the applications of custom vision?

  • How to implement Custom Vision to your application?

    1. Creating a Custom Vision resource to get started
    2. Select the subscription, resource group, region, name, and pricing tier
    3. Upload the existing images of an object to train the model.
    4. Select the "Quick Training" option to quickly prepare the model in minutes
    5. Train an image classification model based on existing images
    6. Publish the model to use it in your applications
  • How to verify the functionalities of the trained model?

    To verify and test the model by running a simple command-line program in the Cloud Shell, real-world solutions, such as web sites or phone applications, use the same ideas and functionalities.

  • Troubleshooting the errors and blockades faced by the attendees throughout the workshop

After the Custom Vision session, there was short FAQ session to answer all the queries regarding custom vision.

QnA Maker


Click the QnA Maker title to view the Microsoft Learn Document for this activity.

In the QnA Maker session, we aimed to create a live chat bot using python by:

  • Understanding what are Chat-bots
  • What are the applications for Chat-bots
  • Create a chat-bot
    1. Creating a QnA Maker resource to get started
    2. Select the subscription, resource group, region, name, and pricing tier
    3. Create a custom question answering knowledge base
    4. Edit the knowledge base
    5. Train and test the knowledge base
    6. Create a bot for the knowledge base
    7. Test the bot to verify its functionalities.


A questioning session was held where students can ask their queries about Microsoft services especially regrading Microsoft Azure and its services. A brief discussion about the Microsoft certifications and how students can leverage Microsoft Learn to excel in the certification exams.

Provision of a roadmap on what their approach should be if they want to make a career in Artificial Intelligence, Data Science, and Cloud Computing.

Take away from this session was to get a hands-on experience on Custom Vision and QnA Maker as service offerings from Microsoft Azure, and build real-time project on the same to showcase on their resume.

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