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Updated in [June 30th, 2023]

This course introduces participants to the concepts of Artificial Intelligence and Machine Learning. It covers the different types and tasks of Machine Learning, as well as the algorithms used to implement them. Participants will explore Python as a popular programming language for Machine Learning solutions, including the use of scientific ecosystem packages to help with implementation.

The course then introduces the Machine Learning tools available in Microsoft Azure. It covers standardized approaches to data analytics and provides specific guidance on Microsoft's Team Data Science Approach. Participants will be introduced to Microsoft's pre-trained and managed Machine Learning offered as REST API's in their suite of cognitive services. They will learn how to implement solutions using the computer vision API and the facial recognition API, and how to do sentiment analysis by calling the natural language service.

Using the Azure Machine Learning Service, participants will create and use an Azure Machine Learning Workspace. They will train their own model, deploy and test it in the cloud. Throughout the course, participants will perform hands-on exercises to practice their new AI skills. By the end of the course, they will be able to create, implement and deploy Machine Learning models.

[Applications]
Upon completion of this course, participants will be able to apply their knowledge of AI and Machine Learning to develop applications on Azure. They will be able to use Python to create machine learning solutions, and use the Azure Machine Learning Service to create, train, and deploy models. Participants will also be able to use the cognitive services offered by Microsoft to perform sentiment analysis, facial recognition, and computer vision.

[Career Path]
Job Position Path:AI Application Developer
Description:AI Application Developers are responsible for developing applications that use Artificial Intelligence (AI) and Machine Learning (ML) technologies. They design, develop, and maintain AI-based applications, and use various programming languages and frameworks to create AI-based solutions. AI Application Developers must have a strong understanding of AI and ML algorithms, and be able to apply them to solve complex problems. They must also be able to work with large datasets and be able to interpret and analyze the data.

Development Trend:The demand for AI Application Developers is expected to grow significantly in the coming years, as more and more businesses are looking to leverage AI and ML technologies to improve their operations. AI Application Developers must stay up-to-date with the latest trends in AI and ML, and be able to develop applications that are able to handle large datasets and complex problems. Additionally, AI Application Developers must be able to work with other developers and stakeholders to ensure that the applications they develop are able to meet the needs of the business.

[Education Path]
The recommended educational path for learners interested in developing AI applications on Azure is to pursue a Bachelor's degree in Computer Science or a related field. This degree will provide learners with the foundational knowledge and skills needed to understand the concepts of Artificial Intelligence and Machine Learning, as well as the tools and technologies used to develop AI applications on Azure.

The Bachelor's degree in Computer Science will cover topics such as programming languages, software engineering, computer architecture, operating systems, databases, and computer networks. Learners will also gain an understanding of the principles of Artificial Intelligence and Machine Learning, including algorithms, data structures, and machine learning models. Additionally, learners will learn about the tools and technologies used to develop AI applications on Azure, such as the Azure Machine Learning Service, cognitive services, and the Team Data Science Approach.

The development trend for this educational path is to focus on the application of AI and Machine Learning in various industries. Learners will gain an understanding of how AI and Machine Learning can be used to solve real-world problems, and how to develop AI applications that can be deployed in the cloud. Additionally, learners will gain an understanding of the ethical implications of AI and Machine Learning, and how to ensure that AI applications are developed responsibly.