This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms. You'll explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning.
About this Course
Learner Career Outcomes
25%
33%
General knowledge of Azure
What you will learn
Define Artificial Intelligence and Machine Language
Describe AI tools and roles, and the Microsoft Team Data Science Process
Work with Azure APIs, including those for vision, language, and search
Create, train, test and deploy your AI model in the cloud
Skills you will gain
Learner Career Outcomes
25%
33%
General knowledge of Azure
Offered by

LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
Syllabus - What you will learn from this course
Introduction to Artificial Intelligence
This module introduces Artificial Intelligence and Machine learning. Next, we talk about machine learning types and tasks. This leads into a discussion of machine learning algorithms. Finally we explore python as a popular language for machine learning solutions and share some scientific ecosystem packages which will help you implement machine learning. By the end of this unit you will be able to implement machine learning models in at least one of the available python machine learning libraries.
Standardized AI Processes and Azure Resources
This module introduces machine learning tools available in Microsoft Azure. It then looks at standardized approaches developed to help data analytics projects to be successful. Finally, it gives you specific guidance on Microsoft's Team Data Science Approach to include roles and tasks involved with the process. The exercise at the end of this unit points you to Microsoft's documentation to implement this process in their DevOps solution if you don't have your own.
Azure Cognitive APIs
This module introduces you to Microsoft's pretrained and managed machine learning offered as REST API's in their suite of cognitive services. We specifically implement solutions using the computer vision api, the facial recognition api, and do sentiment analysis by calling the natural language service.
Azure Machine Learning Service: Model Training
This module introduces you to the capabilities of the Azure Machine Learning Service. We explore how to create and then reference an ML workspace. We then talk about how to train a machine learning model using the Azure ML service. We talk about the purpose and role of experiments, runs, and models. Finally, we talk about
Reviews
TOP REVIEWS FROM DEVELOPING AI APPLICATIONS ON AZURE
The course is brief and very informative. It provides an overall idea regarding Microsoft Azure, project management and end-to-end machine learning from business understanding to deployment.
Great information about AI. Earlier I don't know about AI application too much, but after enrolling in this course I could surely say that you would learn all about AI application.
The best course to learn all the basics of ML and AI...This course very useful in understanding different algorithms and implementations of AI in Microsoft Azure. Thank You !!
Very nicely put course. It gave me good understanding and hands on experience with Microsoft Azure. I got some free credits from Azure to practice what I learned on Coursera.
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