40530: Microsoft Cloud Workshop: Cognitive Services and Deep Learning Course Overview

40530: Microsoft Cloud Workshop: Cognitive Services and Deep Learning Course Overview

The 40530: Microsoft Cloud Workshop: Cognitive Services and Deep Learning course is designed to provide learners with an in-depth understanding of integrating Microsoft Cognitive Services with Azure Machine Learning to create intelligent solutions. Learners explore a real-world customer case study, design a proof of concept, and present their solution in Module 1. This hands-on experience helps participants grasp the practical application of these technologies.

In Module 2, participants dive into the technical aspects: setting up Azure Machine Learning accounts, creating and deploying an unsupervised model, applying TensorFlow, and rounding out their knowledge by completing the solution. This workshop is instrumental for those looking to enhance their skills in AI, machine learning, and Cognitive Computing, and provides a solid foundation for implementing deep learning solutions in the cloud.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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Course Prerequisites

To successfully undertake the 40530: Microsoft Cloud Workshop: Cognitive Services and Deep Learning course, the following minimum prerequisites are recommended:


  • Basic understanding of cloud computing concepts and services, especially within the Microsoft Azure platform.
  • Familiarity with Microsoft Azure services, particularly Azure Machine Learning and Cognitive Services.
  • Experience with any programming language, preferably Python, as it is commonly used in machine learning scenarios.
  • Knowledge of data science and machine learning principles, including an understanding of supervised and unsupervised learning models.
  • Ability to navigate and use the Azure portal to create resources and services.
  • Basic understanding of TensorFlow or other deep learning frameworks is beneficial but not mandatory.
  • An open-minded approach to learning and problem-solving, as the course includes a design and concept proof solution.

These prerequisites are meant to ensure that participants can make the most of the course content and engage with the hands-on lab activities effectively. However, individuals with a strong desire to learn and a commitment to developing their skills in cognitive services and deep learning are encouraged to participate, as foundational knowledge can be built upon during the course.


Target Audience for 40530: Microsoft Cloud Workshop: Cognitive Services and Deep Learning

Course 40530: Microsoft Cloud Workshop on Cognitive Services and Deep Learning focuses on designing and implementing AI solutions using Azure technologies.


Target Audience for Course 40530:


  • Data Scientists and AI Engineers
  • Cloud Solution Architects
  • Software Developers with a focus on AI and machine learning
  • DevOps Engineers interested in deploying AI models
  • IT Professionals looking to expand their knowledge in cognitive services
  • Technical Team Leads managing AI projects
  • AI and Machine Learning Consultants
  • R&D Managers overseeing AI initiatives
  • Technical Decision Makers considering Azure for AI solutions


Learning Objectives - What you will Learn in this 40530: Microsoft Cloud Workshop: Cognitive Services and Deep Learning?

Introduction to Learning Outcomes

This course equips participants with skills to create deep learning solutions using Microsoft Cognitive Services and TensorFlow within Azure. Learners will design, deploy, and integrate AI models into applications.

Learning Objectives and Outcomes

  • Understand the customer case study to identify requirements for a cognitive services solution.
  • Design a proof of concept that integrates Azure Cognitive Services and deep learning to meet business needs.
  • Develop the ability to present and justify solution architecture and design choices effectively.
  • Gain practical experience in setting up Azure Machine Learning accounts and workspaces.
  • Learn to create and deploy unsupervised machine learning models using Azure Machine Learning services.
  • Acquire knowledge on how to apply TensorFlow in building and training deep learning models.
  • Understand the end-to-end process of completing a deep learning solution, from data preparation to model deployment.
  • Explore best practices for integrating cognitive services into applications to add AI capabilities.
  • Ability to troubleshoot common issues in model training and deployment within the Azure environment.
  • Enhance skills in leveraging cloud-based AI services to improve business processes and customer experiences.