Azure Data Science, AI, and ML Training
Master the art of data science, AI, and machine learning on Azure with our comprehensive Azure Data Science courses. Become certified with our official Microsoft Fabric courses, build robust data pipelines with Azure Data Bricks, and become proficient in data engineering on Azure. Our curriculum also covers foundational courses, incluidng Azure Data Fundamentals (DP-900), ensuring you have a solid understanding of the Azure cloud platform.
In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization.
In this Azure Databricks course, participants explore data lake storage integration, database management, Delta Lake fundamentals, and advanced data analysis techniques. The course covers pipeline and job automation and monitoring strategies for optimized performance. Attendees delve into fundamental Big Data principles and practical applications of Apache Spark. Students also get hands-on Azure Databricks experience for data engineering and analysis.
In this Azure Data course, participants explore Azure Data Factory (ADF), Microsoft's cloud-based data integration service. Participants learn ETL (Extract-Transform-Load) fundamentals, pipeline building, and external service integration. Through hands-on exercises, participants master data transformation techniques, orchestration, and monitoring. They also explore the similarities and differences among ADF, Synapse Pipelines, and Fabric.
This course teaches attendees the fundamentals of Azure SQL Database and what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database.
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.
In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.
This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases.
This course teaches developers how to create application using the SQL API and SDK for Azure Cosmos DB. Students will learn how to write efficient queries, create indexing policies, manage and provisioned resources, and perform common operations with the SDK.
This Microsoft Fabric course teaches attendees how to implement and manage enterprise-scale data analytics solutions. Students learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets.
This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric.
This official Microsoft course, Implement Real-Time Analytics with Microsoft Fabric, teaches attendees how to import live data streams from various sources, leverage the power of Eventstream for real-time processing, and unlock insights through KQL queries on data. Students also learn how to create dynamic dashboards that visualize real-time data for effective decision making.
