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.
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.
