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The Microsoft Cloud Workshop: Machine Learning course is a comprehensive program designed for learners to gain hands-on experience in applying machine learning solutions using Microsoft Azure. It consists of two main modules:
Module 1: Whiteboard Design Session - Machine Learning, guides participants through a customer case study, prompting them to design a proof of concept solution and present it, fostering a deep understanding of real-world scenarios.
Module 2: Hands-on lab - Machine Learning, offers practical exercises where learners create models using automated machine learning, delve into model explainability, and work with deep learning models for time series data and text classification. Participants will also explore scoring of streaming telemetry with their forecast models.
By the end of the course, learners will have developed the skills to design and implement robust machine learning solutions, preparing them for challenges in the field of data science and AI.
This is a Rare Course and it can be take up to 3 weeks to arrange the training.
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♱ Excluding VAT/GST
Classroom Training price is on request
♱ Excluding VAT/GST
Classroom Training price is on request
To ensure a successful learning experience in the Microsoft Cloud Workshop: Machine Learning course, participants should come equipped with the following minimum prerequisites:
These prerequisites are designed to ensure that learners can effectively engage with the course content and participate in hands-on lab activities. If you're new to some of these concepts, we recommend exploring introductory materials or courses in cloud computing, Python programming, and machine learning before enrolling in this workshop.
The Microsoft Cloud Workshop: Machine Learning course offers hands-on experience in creating advanced machine learning models, catering to IT professionals and data scientists.
Target audience for the course includes:
This course empowers students with hands-on experience in designing and deploying machine learning solutions using Microsoft Cloud technologies, with a focus on real-world applications and best practices.