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Data Engineering with Microsoft Azure

Nanodegree Program

Master the job-ready skills you need to succeed as a Microsoft Azure data engineer like designing data models and utilizing other in-demand components of the cloud computing service.

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06Days08Hrs48Min47Sec

  • Estimated time
    4 Months

    At 5-10 hours/week

  • Enroll by
    December 14, 2022

    Get access to the classroom immediately upon enrollment

  • Prerequisites
    Experience with SQL, Python, Azure, and Github

What you will learn

  1. Data Engineering with Microsoft Azure

    Estimated 4 months to complete

    Learners will acquire the skills needed to design data models, create data pipelines, and navigate large datasets on the Azure platform. Additionally, they will learn to build data warehouses, data lakes, and lakehouse architecture.

    Prerequisite knowledge

    1. Data Modeling

      In this course, you will find out how to create relational and NoSQL data models to fit the diverse needs of data consumers. Additionally, you’ll understand the differences between different data models and how to choose the appropriate data model for a given situation. Lastly, you’ll build fluency in PostgreSQL and Apache Cassandra.

    2. Cloud Data Warehouses with Azure

      Learn to create cloud-based data warehouses, sharpen data warehousing skills, deepen knowledge of data infrastructure, and understand data engineering on the cloud using Azure.

    3. Data Lakes and Lakehouse with Spark and Azure Databricks

      Learn about the big data ecosystem and how to use Spark to work with massive datasets. You will also store big data in a data lake and develop lakehouse architecture on the Azure Databricks platform.

    4. Data Pipelines with Azure

      Learn to build, orchestrate, automate, and monitor data pipelines in Azure using Azure Data Factory and pipelines in Azure Synapse Analytics. Run data transformations, optimize data flows, and interact with data pipelines in production.

All our programs include:

  • Real-world projects from industry experts

    With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

  • Technical mentor support

    Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

  • Career services

    You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

  • Flexible learning program

    Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Program offerings

  • Class content

    • Real-world projects
    • Project reviews
    • Project feedback from experienced reviewers
  • Student services

    • Technical mentor support
    • Student community
  • Career services

    • Github review
    • LinkedIn profile optimization

Succeed with personalized services.

We provide services customized for your needs at every step of your learning journey to ensure your success.

Get timely feedback on your projects.

  • Personalized feedback
  • Unlimited submissions and feedback loops
  • Practical tips and industry best practices
  • Additional suggested resources to improve
  • 1,400+

    project reviewers

  • 2.7M

    projects reviewed

  • 88/100

    reviewer rating

  • 1.1 hours

    avg project review turnaround time

Learn with the best.

Learn with the best.

  • Matt Swaffer, PhD

    Data Science Practice Lead at Cognitell

    Matt is a data science professional whose career has spanned software development, user experience design, and data visualization. He earned his PhD in the research area of cognitive psychology in human learning and is an adjunct professor teaching software design courses.

  • Amanda Moran

    Developer Advocate at DataStax

    Amanda is a developer advocate for DataStax after spending the last 6 years as a software engineer on 4 different distributed databases. Her passion is bridging the gap between customers and engineering. She has degrees from the University of Washington and Santa Clara University.

  • Vishnu (Lucky) Pamula

    Sr. Cloud Solution Architect at Microsoft

    Lucky is a data & AI evangelist with a track record of successfully helping organizations build analytics solutions. Besides his day job, he teaches as an adjunct professor, delivers lunch & learns, mentors students, and evangelizes Azure Quantum as an ambassador.

Data Engineering with Microsoft Azure

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Data Engineering with Microsoft Azure

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