65 Hours


In this Data Engineering microcredential course, learners will master batch and real-time analytics using Azure’s data platform technology. It begins with core computing and storage concepts, followed by interactive data exploration in data lakes. Learner will have a knowledge on data ingestion techniques with tools like Apache Spark in Azure Synapse Analytics, Azure Databricks, Azure Data Factory, and Azure Synapse pipelines. The course also covers data transformation using these tools, emphasizing data security. Finally, learners will create real-time analytics systems for faster, more precise insights. This course offers hands-on experience and a robust foundation in data engineering.

Course Outline

Module 1: Get Started with Data Engineering on Azure

Module 2: Build data analytics solutions using Azure Synapse serverless SQL pools

Module 3: Perform data engineering with Azure Synapse Apache Spark Pools

Module 4: Work with Data Warehouses using Azure Synapse Analytics

Module 5: Transfer and transform data with Azure Synapse Analytics pipelines

Module 6: Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics

Module 7: Implement a Data Streaming Solution with Azure Stream Analytics

Module 8: Govern data across an enterprise

Module 9: Data engineering with Azure Databricks

Required Resources

Laptop, Intel Core i5 or higher, 16GB, 1TB Storage, Graphics Card (Hardware); Microsoft Azure (Software); Adequate Internet Connection (Network)


The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course are data analysts and data scientists who work with analytical solutions built on Microsoft Azure.


In this Data Engineering course, there will be

  • One (1) diagnostic assessment is conducted synchronously and is knowledge-based, with the flexibility for learners to choose between remote or on-site participation.
  • Two (2) formative assessments, one focused on knowledge and the other on performance. Both are available asynchronously, allowing learners to complete them at their own pace and participate remotely or on-site.
  • A performance-based summative assessment is conducted synchronously, providing learners with remote or on-site participation.

Credit and Recognition

Upon completing the Data Engineering course, learners will receive a Certificate of Completion and a badge. These serve both as a recognition of acquired data science expertise and a foundational step toward more advanced studies in said field.

This course is facilitated by a Microsoft Certified Professional, someone who has completed professional training for Microsoft products through a certification program provided by Microsoft. To ensure the quality of this microcredential, continuous feedback loops with students, instructors, and industry practitioners are maintained to improve content, delivery, and assessment methods continuously.

Learning Pathways

The learner is eligible to take the Microsoft Certified: Azure Data Engineer Associate.
Data Engineering Path: Data Management is your prerequisite for entering the world of Data Engineering, where you’ll learn how to architect and manage data pipelines efficiently. Data Engineering is an essential step toward mastering Machine Learning.

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