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Microsoft Cloud Workshop: Machine Learning Course Overview

Microsoft Cloud Workshop: Machine Learning Course Overview

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.

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  • Live Training (Duration : 8 Hours)
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Free Pre-requisite Training

Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.

Assessments (Qubits)

Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.

Post Training Reports

Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.

Class Recordings

Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.

Free Lab Extensions

Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.

Free Revision Classes

Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

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♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

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Target Audience for Microsoft Cloud Workshop: Machine Learning

  1. The Microsoft Cloud Workshop: Machine Learning course offers hands-on experience in creating advanced machine learning models, catering to IT professionals and data scientists.


  2. Target audience for the course includes:


  • Data Scientists
  • Machine Learning Engineers
  • AI/ML Researchers
  • Data Analysts
  • IT Professionals with an interest in machine learning
  • Cloud Solutions Architects
  • Software Engineers looking to specialize in machine learning
  • DevOps Engineers focusing on machine learning pipelines
  • Technical Team Leaders managing machine learning projects
  • Product Managers overseeing ML-based products
  • Consultants providing machine learning solutions
  • Technical Sales Professionals involved in AI/ML solutions


Learning Objectives - What you will Learn in this Microsoft Cloud Workshop: Machine Learning?

Introduction to Course Learning Outcomes and Concepts Covered

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.

Learning Objectives and Outcomes

  • Understand the customer case study to align machine learning solutions with business requirements.
  • Design a proof of concept for a machine learning solution that addresses a real-world problem.
  • Develop presentation skills to effectively communicate the designed solution to stakeholders.
  • Acquire practical skills in creating forecast models using Azure's automated machine learning capabilities.
  • Learn to interpret machine learning models and their predictions using model explainability tools.
  • Gain experience in building and training deep learning models, specifically Recurrent Neural Networks (RNNs), for time series analysis.
  • Master the process of registering and managing machine learning models within the Azure ecosystem.
  • Implement techniques for real-time scoring of streaming data using trained forecast models.
  • Construct deep learning models for text classification, enhancing the ability to process and analyze textual data.
  • Explore best practices for deploying and operationalizing machine learning models in a cloud environment.

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