This course will teach the basics of Microsoft’s dialect of the standard SQL language: Transact-SQL. Topics include both querying and modifying data in relational databases that are hosted in Microsoft SQL Server-based database systems, including: Microsoft SQL Server, Azure SQL Database and, Azure Synapse Analytics.

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.

Did you know that over 95% of Fortune 500 companies use Microsoft Azure to manage their cloud infrastructure? Are you equipped to administer critical SQL workloads in the cloud?

In this course, you’ll learn to administer SQL Server databases across IaaS, Azure SQL Database in PaaS, and hybrid environments. You’ll configure high availability, secure sensitive data, migrate workloads, and fine-tune performance, skills that directly support>real-world database administration success.

This course also gets you ready for the DP-300 exam, a key step toward earning your Microsoft Certified Azure Database Administrator Associate credential, which proves you have the skills to manage modern database solutions on the Microsoft data platform.

Organizations today rely on data-driven decision-making, but managing massive datasets across cloud platforms can be complex. DP-3011 Implementing a Data Analytics Solution with Azure Databricks equips data professionals to prepare, analyze, and govern data at scale using Apache Spark’s distributed computing capabilities.

In this one-day training, you’ll gain hands-on experience with Delta Lake for versioning and data integrity, automate data pipelines with Delta Live Tables, and implement governance with Unity Catalog. You’ll also explore Spark for large-scale data analysis, orchestrate workflows for production deployments, and collaborate in Python and SQL notebooks to deliver high-quality analytics-ready data.

Azure Databricks is a fully managed, cloud-based data analytics platform, which empowers developers to accelerate AI and innovation by simplifying the process of building enterprise-grade data applications. Built as a joint effort by Microsoft and the team that started Apache Spark, Azure Databricks provides data science, engineering, and analytical teams with a single platform for big data processing and machine learning. In this course, you’ll learn how to use Azure Databricks to train and deploy machine learning models.

This course teaches developers to utilize Azure Cosmos DB for NoSQL API and SDK. Students will learn query execution, resource configuration, SDK operations, and design strategies for non-relational data modeling and data partitioning.