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AI Engineer Using Microsoft Azure

Introducing AI Engineer Using Microsoft Azure Nanodegree Program from Udacity

Udacity is excited to introduce the newest addition to our School of Artificial Intelligence: the AI Engineer Using Microsoft Azure Nanodegree program. This program is designed to train people who are interested in becoming an Azure AI engineer or an AI engineer with expertise in Azure AI and machine learning (ML) services. 

Students will learn how to implement ML models, design and build end-to-end AI solutions using Azure Cognitive Services, as well as deploy, monitor, and improve existing Azure AI solutions. After completing this course, students will become ideal candidates for the Microsoft certification AI-102.

What is Microsoft Azure?

Microsoft Azure is Microsoft’s cloud solution platform. It has over 200 products and cloud services to help companies build applications and store data securely. Their users range from Fortune 500 companies to government and healthcare industries around the globe. 

Learning how to work as an AI Engineer specializing in Microsoft Azure will instantly put you in a great spot career-wise. AI Engineers are responsible for using Microsoft Azure cloud services — specifically in AI, machine learning, computer vision, knowledge mining, natural language processing (NLP), and more!

AI Engineer Using Microsoft Azure Nanodegree Program Details

The AI Engineer Using Microsoft Azure Nanodegree program will prepare you to:

  • Design and build an end-to-end AI solution using Azure Cognitive Services and Azure Cognitive APIs
  • Design a security strategy that aligns with organizational policies and compliance frameworks
  • Deploy, monitor, and manage continuous improvement of an Azure AI solution

To get the most out of this course, it’s important for students to have at least intermediate Python programming skills — including understanding object-oriented programming (OOP), knowing Python syntax, data types, and basic algorithms. Familiarity with Microsoft Azure is also recommended, especially with Azure data sources, like the Azure Data Lake and Azure SQL. Finally, it’s important for enrollees to be comfortable with JSON and REST programming semantics for the use with APIs.

In as little as three months (at 5-10 hours a week), students who enroll in the AI Engineer Using Microsoft Azure Nanodegree program will learn how to use computer vision technology with vision-based Azure Cognitive Services, build NLP and conversational AI solutions using Azure QnA Knowledge Bases and LUIS Models, and design knowledge mining solutions using Azure Cognitive Search.

Specific projects include:

Project 1: Automated Passenger Boarding Kiosk

Students will build an automated passenger boarding kiosk that collects passenger and flight information through the passenger’s photo, digital ID, or boarding pass. The application must be able to validate and confirm if a given passenger can board the plane or not using Azure Cognitive Services including Azure Computer Vision, Face, Form Recognizer, Video Analyzer, and Azure Blob storage.

Project 2: Dental Office Virtual Assistant

Create a customer support chatbot for a dentist website using a Bot on the Azure platform. Their bot will be built with a Node.js bot application, a trained LUIS model, and a QnA Knowledge Base. The bot will have the ability to answer questions and schedule appointments. Once the bot is working and tested, students will deploy the bot application and resources to Azure and implement it on a website.

Project 3: Build an AI Enriched Corporate Training Catalog

Combine four different datasets: a set of Udacity courses, a set of Microsoft Learn courses, a generated set of corporate training, and a set of open-source papers to create a large dataset of training materials. Then, students will enrich these data using OCR, key phrase extraction, custom entity recognition, and custom skills. Finally, they will attach a user-facing search interface to help users search for solutions. 

Learning from Top AI Engineers

To develop this program’s world-class curriculum, we collaborated with professionals from top-rated tech companies. Each of these collaborators contributed guidance and feedback to focus the program on the most in-demand skills. Each of the instructors has extensive AI, Microsoft Azure, and teaching experience. 


  • Avkash Chauhan, Founder and Principal at
  • Valerie Scarlata, Curriculum Manager at Udacity
  • Matt Swaffer, Solutions Architect at Managed Business Solutions

Enroll in the AI Engineer Using Microsoft Azure Nanodegree Degree

If you’re a current ML or AI engineer who wants to gain experience developing in Microsoft Azure, or if you’re a current Azure cloud or solutions architect and want to learn more about AI engineering, this Nanodegree program is for you. 

Additionally, this course could be well suited for data engineers looking to transition into an AI or ML-focused role, or any software engineer looking to become an AI Engineer.

There’s never been a better time to get into the field of AI and ML engineering. AI is one of the fastest-growing and most transformational technologies of our time, having added over 2.3 million new jobs in the past few years. According to ZipRecruiter, AI Engineers make an average annual salary of over $164,000 a year. That’s a high salary, even for tech in general!

With Udacity’s combination of hands-on project-centric learning and expert mentorship, there’s no better way to meet the demand than by registering today for the AI Engineer Using Microsoft Azure Nanodegree program. Enroll now to learn more!

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