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.
What You’ll Learn
Upon completing this course, you will have the proficiency to conceive and execute different phases and principles within the data engineering lifecycle, encompassing storage, processing, and security, within the Microsoft Azure ecosystem. Moreover, you will be empowered to develop and execute data service operations, including monitoring and optimization, effectively within Microsoft Azure.
Skills You’ll Gain
- Data science
- Azure
Roles
- Data Engineer
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)
Pre-Requisites
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.
Assessment
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.
Specifically:
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.
