The latest addition to Udacity's ever-expanding list of Nanodegrees is a great opportunity to build a portfolio of AI projects using Microsoft Azure. Its inaugural session starts on February 2nd.

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AI Engineer Using Microsoft Azure is a 3-month Nanodegree Program offered by Udacity in collaboration with Microsoft. 

If you aren't familiar with Udacity, as outlined recently in Gain New Skills With Udacity, it offers an intensive, highly practical and hands-on learning experience and can be considered the large-scale online equivalent of a Boot Camp. Udacity's distinctive credential is the Nanodegree, earned by successful completion of a series of projects, and it works with industry partners to ensure that each program is relevant to specific job roles.

According to its overview:

The AI Engineer Using Microsoft Azure Nanodegree program will equip students with the skills required to become an Azure AI engineer or an AI engineer with expertise in Azure AI and machine learning services. This program will teach students how to implement machine learning models, design and build an end-to-end AI solution with Azure Cognitive Services, and how to deploy, monitor, and manage continuous improvement of an Azure AI solution. Students seeking certification who successfully complete this program are ideal candidates for Microsoft certification A1-102. 

AI and Cloud Computing are both on the current list of in-demand skills and we have heard repeatedly that certification can boost your career. So discovering that this program is good preparation for the Microsoft Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution makes it doubly worth contemplating for "upskilling" - something that many employers are keen on investing in in order to retain their existing workforce. The Syllabus also makes it sound a very interesting challenge.

AI Engineer Using Microsoft Azure is comprised of three courses, each of which includes a project:

Course 1: Building Computer Vision Solutions with Azure
Project: Automated Passenger Boarding Kiosk

You will begin by learning what computer vision is and and how it works through real-life business use cases. You will then learn to create solutions using different types of vision-based Azure Cognitive Services, including Azure Form Recognizer for text extraction, Azure Face and Video Analyzer for facial detection and recognition, and Azure Computer Vision and Custom Vision for image classification and object detection. Finally, you will learn and apply deployment and monitoring tools to ensure that your solution is complete and runs smoothly.

Course 2: Building NLP and Conversational AI Solutions with Azure
Project: Dental Office Virtual Assistant

You’ll begin by exploring use cases for NLP and conversational AI, including chatbots and assistant solutions. Then you’ll create solution diagrams, model dialogs, and learn about responsible AI principles and practice creating requirements for conversational applications. You’ll create and configure bot applications on the Azure platform using the Microsoft Bot Framework and integrate Azure QnA Knowledge Bases and LUIS Models. In the last part of the course you’ll implement Azure Text and Speech Cognitive Services in applications.

Course 3: Building Knowledge Mining Solutions With Azure Cognitive Search
Project: Build an AI Enriched Corporate Training Catalog

In this course, you will learn how to add data sources to Azure Cognitive Search, enrich the data with AI, properly index the enriched data, and expose the index to client applications for search scenarios. You will begin by learning how to design an Azure Cognitive Search solution and finish the course by building out an AI-enriched data mining application from end to end.

So what do you already need to know before you can embark on this program? Udacity recommends its free course AI Fundamentals free course for the gaining useful knowledge of AI and the program's prerequisites are Python programming skills,  knowledge of Microsoft Azure and the ability to navigate the Azure portal and familiarity with a variety of Azure data sources such as Azure Data Lake and Azure SQL. You also need the ability to use APIs in application development and knowledge of JSON and REST programming semantics.  

The AI Fundamentals course is also jumping off preparation for Machine Learning Engineer for Microsoft Azure another Microsoft-supported 3-month Nanodegree in which students  build and deploy sophisticated machine learning solutions using popular open source tools and frameworks, and gain practical experience running complex machine learning tasks using Azure labs.

If neither of these Nanodegrees fit your requirements, see Gain New Skills With Udacity where I outlined:

• AWS Machine Learning Engineer
• Artificial Intelligence Nanodegree
• Foundations of Computer Vision Nanodegree 
• Natural Language Processing Nanodegree

More Information

AI Engineer Using Microsoft Azure

 Machine Learning Engineer for Microsoft Azure

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