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Microsoft Cloud Workshop: Azure Synapse Analytics and AI Course Overview

Microsoft Cloud Workshop: Azure Synapse Analytics and AI Course Overview

The Microsoft Cloud Workshop: Azure Synapse Analytics and AI course is an immersive training experience that focuses on building a comprehensive understanding of how to integrate Azure Synapse Analytics with AI capabilities. Participants engage in a collaborative whiteboard design session to review a customer case study, design a proof of concept solution, and present their solution, which emphasizes practical problem-solving and architectural designs.

In the hands-on lab, learners dive into the Azure Synapse Analytics workspace, managing and populating SQL Pool tables, and exploring various data formats using serverless SQL capabilities. The lab also covers Synapse Pipelines, Cognitive Search integration, implementing security, applying machine learning techniques, and monitoring resources. This synapse training course is an excellent resource for anyone looking to enhance their azure synapse analytics training and gain practical experience with Azure's analytics and AI tools.

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

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  • Live Online Training (Duration : 8 Hours)
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  • Live Online Training (Duration : 8 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To ensure that participants can successfully engage with and benefit from the Microsoft Cloud Workshop: Azure Synapse Analytics and AI course, the following minimum prerequisites are recommended:


  • Basic understanding of cloud computing concepts and experience with Microsoft Azure services.
  • Fundamental knowledge of data warehouse concepts and familiarity with relational databases.
  • Experience with data processing and ETL (Extract, Transform, Load) operations.
  • Basic understanding of machine learning concepts and analytics.
  • Familiarity with SQL and experience in writing SQL queries.
  • An introductory level of knowledge in Python or another programming language for machine learning modules.
  • General knowledge of data security principles.

These prerequisites are designed to provide a foundation upon which the course content can build. They are not meant to be barriers to entry but rather to ensure a productive and enriching learning experience.


Target Audience for Microsoft Cloud Workshop: Azure Synapse Analytics and AI

The Microsoft Cloud Workshop: Azure Synapse Analytics and AI course is aimed at professionals seeking advanced analytics and AI skills using Azure.


  • Data Scientists and Data Engineers
  • Analytics Consultants
  • BI Professionals and Data Analysts
  • Database Administrators and Architects
  • IT Professionals with a focus on data solutions
  • Cloud Solution Architects
  • AI Engineers
  • DevOps Engineers with an interest in data pipelines and analytics platforms
  • Technical Team Leads managing data-driven projects
  • Business Intelligence Developers
  • Technical Project Managers involved in analytics projects


Learning Objectives - What you will Learn in this Microsoft Cloud Workshop: Azure Synapse Analytics and AI?

Introduction to Learning Outcomes and Concepts Covered:

Gain practical skills in Azure Synapse Analytics and AI through a comprehensive workshop, focusing on designing solutions and hands-on experience with data integration, machine learning, and security in Azure.

Learning Objectives and Outcomes:

  • Understand the customer case study to identify business requirements and challenges for implementing Azure Synapse Analytics and AI solutions.
  • Design a proof of concept (PoC) solution that leverages Azure Synapse Analytics to address the specific needs presented in the case study.
  • Develop presentation skills to effectively communicate the designed solution to stakeholders.
  • Access and navigate the Azure Synapse Analytics workspace to familiarize with the environment.
  • Create and manage databases, tables, and processes to populate SQL pools with data for analytics.
  • Explore and analyze raw data formats like parquet and text using Azure Synapse SQL Serverless capabilities.
  • Implement Synapse Pipelines to automate data movement and integration tasks.
  • Utilize Azure Cognitive Search to enhance data discoverability and insights through AI-enriched search capabilities.
  • Apply security best practices within Azure Synapse Analytics to protect data and manage access controls.
  • Integrate machine learning models into the analytics pipeline, leveraging Azure Synapse for advanced analytics.
  • Monitor and optimize Azure Synapse Analytics resources to ensure efficient and cost-effective operation of the analytics environment.