Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets.
Overview
Syllabus
- Welcome to the Data Engineering with AWS Nanodegree Program
- Welcome!
- Data Modeling
- Learn to create relational and NoSQL data models to fit the diverse needs of data consumers. Use ETL to build databases in PostgreSQL and Apache Cassandra.
- Cloud Data Warehouses
- In this course, you’ll learn to create cloud-based data warehouses. You’ll sharpen your data warehousing skills, deepen your understanding of data infrastructure, and be introduced to data engineering on the cloud using Amazon Web Services (AWS).
- Spark and Data Lakes
- In this course, you will learn about the big data ecosystem and how to use Spark to work with
massive datasets. You’ll also learn about how to store big data in a data lake and query it with Spark. - Automate Data Pipelines
- Schedule, monitor, and manage data workflows efficiently using tools like Apache Airflow. Build data pipelines by leveraging Airflow DAGs to organize tasks and utilize AWS resources such as S3 and Redshift to process and move data effectively between systems. Engage in hands-on projects to automate and maintain complex data pipelines, streamlining operations and improving data reliability. Gain expertise in workflow automation, data integration, and error handling, enabling you to construct efficient and scalable data pipelines in production environments. Ideal for data engineers and professionals aiming to advance their skills in managing and automating data workflows.
- Congratulations!
- Congratulations on finishing your program!
Taught by
Amanda Moran, Ben Goldberg, Sameh El-Ansary, Olli Iivonen, David Drummond, Judit Lantos, Juno Lee , Rodrigo G., Andrew M., Stanislav V., Eugenio C., Nitheesha T. and Jitesh S.
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Reviews
5.0 rating, based on 7 Class Central reviews
4.6 rating at Udacity based on 1248 ratings
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The project gave me a better knowledge about OLAP vs. OLTP, normalization, denormalization, and how to implement it into practice. I have been working in Data Engineering field for 3 years, but the program has given me a clear understanding about why we need those concepts in DE fields.
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Data Engineering at Udacity is quite interesting, cool interface/videos and all lessons are well structured with real life project.
I love the project , the reviewers comments and generally the way it was reviewed! -
Really enjoyed the course. I had some previous knowledge of some of the topics, but there were still things I learned from the course. The projects were well-designed and gave me the feeling to be working on some semi-realistic scenario without being too hard.
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This course is highly essential for anyone who wants to become a data engineer. I enjoyed the projects and exposure to various data engineering tools. It gives one the right foundation to build on.
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I'm working as dwh engineer and want to forward to check how data engineer stuff going on and I did some research about which course or programm I should start study on then I find udacity and few other programms and compare them by content difference , which tools they are using while course going on ,which technologies they are prefer to apply and how these are fits to real life scenarios and belive me the one of most important point is evaluation proccess of your projects and asking questions to MENTORS (till now I can't see any question not answered). I see udacity far best ! . I advice you to check udacity courses before you decide to start.
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I've just completed the first project. The project was great since it's what you'd expect to be able to do at work, and the reviewer's comments and guidance were helpful and informative!
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I am very happy with the content and this first project has helped me a lot to better understand the technical concepts. Thank you!
