Audience
This workshop is intended for Cloud Architects and IT professionals who have architectural expertise of infrastructure and solutions design in cloud technologies and want to learn more about Azure and Azure services as described in the “Summary” and “Skills gained” areas.
Prerequisites
Those attending this workshop should also be experienced in other non-Microsoft cloud technologies, meet the course prerequisites, and want to cross-train on Azure.
Course outline
Module 1: Whiteboard Design Session – Machine Learning
Lessons
• Review the customer case study
• Design a proof-of-concept solution
• Present the solution
Module 2: Hands-On lab – Machine Learning
Lessons
• Creating a forecast model using automated machine learning
• Understanding the automated ML generated forecast model using model explainability
• Creating a deep learning model (RNN) for time series data and registering the model
• Using a forecast model for scoring of streaming telemetry
• Creating a deep learning text classification model
Schedule
Click on the following link to see the current Course Schedule
Our minimum class-size is 3 for this course.
If there are no scheduled dates for this course, it can be customized to suit the time and skill needs of clients and it can be held online, at a rented location or at your premises.
Click on the following link below to arrange for a custom course: Enquire about a course date
FAQs
CERTFICATE OF COMPLETION: Participants will receive a certificate of completion at the end of a course. This is not an official certification for the product and/or software. Our courses do indicate the appropriate certification exam(s) that the participant can sit. Data Vision Systems does not provide certification or deliver the certification exams. Participants are responsible for arranging and paying for the certification exams on the appropriate certification body.
CANCELLATION POLICY: There is never a fee for cancelling seven business days before a class for any reason. Data Vision Systems reserves the right to cancel any course due to insufficient registration or other extenuating circumstances. Participants will be advised prior to doing so.
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