This course bundle will provide you with a foundation of practical knowledge on artificial intelligence (AI) and machine learning. You will begin with the science behind AI computer systems, which can perform tasks that typically require human intelligence, and AI ethics, applications, and more.
This course bundle will provide you with a foundation of practical knowledge on artificial intelligence (AI) and machine learning. You will begin with the science behind AI computer systems, which can perform tasks that typically require human intelligence, and AI ethics, applications, and more.
Then you will move on to a more thorough look at machine learning, the problem it is trying to solve, and specific techniques and applications used in supervised, unsupervised, and semi-supervised learning.
About Us
This program will enable students to further their education in computer science by specializing in problem-solving and data management in an artificial intelligence environment, particularly in machine learning.
Taking ML models from conceptualization to production is typically complex and time-consuming. You have to manage large amounts of data to train the model, choose the best algorithm for training it, manage the compute capacity while training it.
You will discover how to differentiate offline and online training and predictions, automated machine learning, and how the cloud environment affects machine learning functions. Additionally, you will explore some of the most significant areas in the field of machine learning research.
The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure's premier data science service, the Azure Machine Learning service, to automate the data science pipeline.
Learn how to use notebooks and scripts to train machine learning models and use Azure Machine Learning services to assess data, manage compute, track training models, implement Responsible AI principles, and deploy models to endpoints.
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