Introduction to Data Engineering an Azure
This topic provides an overview of data engineering concepts and their implementation on the Azure platform. It covers the basics of data storage, processing, and management in the cloud environment.

Azure Data Lake Storage Gen2 
This is a cloud-based data storage solution that provides secure, scalable, and cost-effective storage for big data analytics workloads. It enables users to store and analyze data of any size, shape, and speed in one single location.

Azure Synapse Analytics
This is an analytics service that brings together big data and data warehousing. It provides an end-to-end solution for data ingestion, preparation, management, and serving, with integrated security and governance.

Azure Databricks

This is a collaborative, cloud-based platform for data engineering, machine learning, and analytics. It provides a unified workspace for data scientists and engineers to build, train, and deploy machine learning models at scale.

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Data Science with Azure

This topic covers the basics of data science and how it can be applied to real-world problems using Azure tools and services. It includes data preparation, visualization, statistical analysis, and predictive modeling.

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Machine Learning Models

This topic focuses on the building and deployment of machine learning models using Azure Machine Learning. It covers the entire machine learning workflow, from data preparation to model evaluation and deployment.