Everything you need to become a Data Engineer

or get better at Engineering

Beginner Friendly

All courses are beginner friendly and vary from single courses to complete example projects.

On-Demand Access

Choose your own learning pace and access to content on-demand.

New Content

Academy content is constantly expanded and we usually release a new course every month

Here's what you can achieve in the next 3 months:

In 1 Month: Data Engineering Fundamentals

After one month you know what Data Engineers do exactly, have the technical computer science fundamentals, Python coding and Docker skills.

Plus the theoretical knowledge of how to design data platforms & pipelines and how to choose the right data store and do a schema design.

Gain all the fundamentals you need to do hands on projects.

Learn what Data Engineers do exactly, gain the technical the computer science fundamentals, Python coding and Docker skills.

Plus the theoretical knowledge of how to design data platforms & pipelines, how to choose the right data store and do a schema design.

In 3 Months: Build an Open Source Platform

After 3 months you built an awesome Open Source platform with tools like FastAPI, Apache Kafka, Apache Spark streaming, MongoDB and Streamlit. This will help you get into Data Engineering without a cloud platform subscription.

Depending on your speed or interests you can also add knowledge in orchestrating pipelines with Airflow, process time series data with InfluxDB, monitor pipelines with Elasticsearch and build a Elasticsearch contact tracing app.

After 3 months you built an awesome Open Source platform with tools like FastAPI, Apache Kafka, Apache Spark streaming, MongoDB and Streamlit. This will help you get into Data Engineering without a cloud platform subscription.

Depending on your speed or interests you can also add knowledge in orchestrating pipelines with Airflow, process time series data with InfluxDB, monitor pipelines with Elasticsearch and build a Elasticsearch contact tracing app.

Or in 3 Months: Data Engineering on AWS

Instead of going open source you gain extensive AWS experience by building your own stream and batch processing platform including deploying containerized apps like ML algorithms on AWS.

You will know how to work with all major tools like API Gateway, Kinesis, Lambda, AWS Glue, S3, DynamoDB, Redshift, Cloudwatch, RDS, Elastic Container Registry and Service.

If you take the open source and AWS tracks you will also be able to complete our Associate Data Engineer certification.

Instead of going open source you gain extensive AWS experience by building your own stream and batch processing platform including deploying containerized apps like ML algorithms on AWS.

You will know how to work with all major tools like API Gateway, Kinesis, Lambda, AWS Glue, S3, DynamoDB, Redshift, Cloudwatch, RDS, Elastic Container Registry and Service.

If you take the open source and AWS tracks you will also be able to complete our Associate Data Engineer certification.

Plus: Modern Data Warehouses and Azure Streaming

Your schedule is fully customizable. Either with annual or unlimited access you have enough time to get familiar buiding streaming pipelines on Azure or Data Warehousing on AWS, GCP, Databricks and Hadoop if you are interested in that.

Within 3 to 4 weeks you can easily also gain the knowlege to work with AWS Athena and Quicksight, GCP BigQuery and Datastudio or build ETL pipelines and Warehouses on Databricks.

Within 2 weeks you will know the basics of Azure and be able to build streaming pipelines with API Management, EventHub, Function Apps, CosmosDB and PowerBI.

Your schedule is fully customizable. Either with annual or unlimited access you have enough time to get familiar buiding streaming pipelines on Azure or Data Warehousing on AWS, GCP, Databricks and Hadoop if you are interested in that.

Within 3 to 4 weeks you can easily also gain the knowlege to work with AWS Athena and Quicksight, GCP BigQuery and Datastudio or build ETL pipelines and Warehouses on Databricks.

Within 2 weeks you will know the basics of Azure and be able to build streaming pipelines with API Management, EventHub, Function Apps, CosmosDB and PowerBI.

Huge Catalog!

From basics to full hands-on example projects.

All individually available in the Academy

1. The Basics

We start with the basics you need to learn Data Engineering. From what is Data Engineering, the computer science fundamentals, to how document your journey.

Video Time Available: 7h

  • 1.1Introduction to Data Engineering
  • 1.2Computer Science Fundamentals
  • 1.3Introduction to Python
  • 1.4Python for Data Engineers
  • 1.5Docker Fundamentals
2. Platform & Pipeline Design Fundamentals

The second part teaches you the fundamentals of platform and pipeline design, how to incorporate security, the different types of data stores and schema design.

Video Time Available: 3.75h

  • 2.1Platform & Pipeline Design
  • 2.2Platform Security
  • 2.3Choosing Data Stores
  • 2.4Schema Design
  •  
3. Fundamental Tools

Module three contains fundamental tools who you are going to see all the time. From data ingestion, message queues, processing frameworks to visualization.

Video Time Available: 9.75h

  • 3.1API Fundamentals with FastAPI
  • 3.2Apache Airflow Workflow Orchestration
  • 3.3Apache Spark Fundamentals
  • 3.3Data Engineering on Databricks (NEW!!!)
  • 3.4Apache Kafka Fundamentals
  • 3.5MongoDB Document Store Fundamentals
  • 3.6Log Analysis With Elasticsearch
  •  
4. Example projects

To apply what you have learned you can do a variety of hands-on example projects on AWS, Azure and your own computer.

Video Time Available: 21h

  • 4.1Document Streaming with Kafka, Spark & MongoDB
  • 4.2Data Engineering on AWS
  • 4.3Machine Learning & Containerization on AWS
  • 4.4Data Engineering on Azure
  • 2.5Modern Data Warehouses & Data Lakes
  • 4.6Storing & Visualizing Time Series Data
  • 4.7Contact tracing with Elasticsearch
  • 4.8Data Engineering on Hadoop

Join the Data Engineering Academy

The step by step course to learn Data Engineering with prepared example projects and courses on specific tools.
It links together all courses in the academy. Constantly new content!

or

Choose your plan for Data Engineering Academy

Get full access to the Academy and all courses!
All these benefits are included:
  • Huge Step by step Data Engineering Course
  • Unlimited access to all current and future courses
  • We typcially release one new course every month
  • 5 theory courses on the most important engineering techniques
  • 10 hands-on courses the most important tools for engineers
  • 8 hands-on example data engineering projects on major platforms like AWS, Azure, Hadoop and open source platforms
  • Associate Data Engineer Certification & course certificates
  • Individual course certificates
  • Personal support on your journey over our private Discord server

Group Discounts: If you're interested in signing up with your team -
ask about our group discounts here: Group Discount Application

      Your personal price:
      $685.44

      $261.80

      Money back guarantee if you don't like it.

      What my students say

      Godwin E.

      Great course by Andreas, my favorite part of the course are the example projects, it gives you the understanding of how data engineering is done in the real world, also get to have a portfolio of projects across different cloud platforms. 

      Andy N.

      Andreas's method of targeting skills that are in demand and building projects around them is the fastest way to get a job in Data Engineering. I was able to get a job in 2 months. Thanks Andreas.

      Ritesh C.

      I appreciate the way Andreas has been able to identify and bring forward real concepts that help understand the overall subject better. He covers a lot of contemporary tools and tech in small capsule courses that are easy to understand and build upon. Glad to have opted in.

      Here's what is coming soon:

      Snowflake Fundamentals

      Whenever you hear data warehouse and cloud Snowflake is not far. Togehter with Databricks Snowflake is the biggest competitor to AWS, Azure and GCP especially in the warehousing sector.

      In this course you will learn all the fundamentals of Snowflake including fundamental concepts and a great hands-on part that gets you started quickly.

      Release: October 2022

      Whenever you hear data warehouse and cloud Snowflake is not far. Togehter with Databricks Snowflake is the biggest competitor to AWS, Azure and GCP especially in the warehousing sector.

      In this course you will learn all the fundamentals of Snowflake including fundamental concepts and a great hands-on part that gets you started quickly. Release 2nd half of 2022

      MLOps on AWS using GitHub

      In our Machine Learning and containerization project you learned how easy it is to deploy a NLP algorithm as Lambda function and a visualization as containerized app on AWS ECS.

      In this project you learn how to take it to the next level. You learn how to Use GitHub, GitHub Actions and AWS CDK to package your algorithm into a Docker container and deploy it as an API on AWS.

      Release: Nov. 2022

      In our Machine Learning and containerization project you learned how easy it is to deploy a NLP algorithm as Lambda function and a visualization as containerized app on AWS ECS.

      In this project you learn how to take it to the next level. You learn how to Use GitHub, GitHub Actions and AWS CDK to package your algorithm into a Docker container and deploy it as an API on AWS.

      This way you can see the sentiment of Tweets on your dashboard and an update to the algorihm is only a git commit away.

      Transforming Data with dbt

      Transforming data in your data warehouse is super important. And dbt is THE tool right now.

      In this course you will learn the fundamentals of dbt and the dbt platform. You will connect dbt to GCP BigQuery and run jobs to transform data.

      Release: Dec 2022 - Jan 2023

      In our Machine Learning and containerization project you learned how easy it is to deploy a NLP algorithm as Lambda function and a visualization as containerized app on AWS ECS.

      In this project you learn how to take it to the next level. You learn how to Use GitHub, GitHub Actions and AWS CDK to package your algorithm into a Docker container and deploy it as an API on AWS.

      This way you can see the sentiment of Tweets on your dashboard and an update to the algorihm is only a git commit away.

      Frequently Asked Questions

      Why join Learn Data Engineering?

      Unlike typical online course, the content on Learn Data Engineering grows every week. Andreas and other trainers are constantly adding new topics, videos and worksheets.

      Is Learn Data Engineering right for me?

      Our academy is right for you if you are interested in the plumbing of Data Science. We have helped many members and coaching students who work as Data Scientist, Data Analyst, Database Administrator, Software Developer as well as graduates who are searching for Data Engineering jobs or want to apply the skills in the future.

      How long do I have to complete the course?

      The courses in our academy are all completely on-demand, which means you can advance the courses and their modules at your own pace. You can start whenever you want, and there are no deadlines to finish. If you have questions just use our Slack group to get help.

      What prior knowledge should I have for the course?

      The optimal foundation for Data Engineering is having prior computer science knowledge. As a Data Engineer you need to be able to code and use SQL to talk to databases. Don’t worry though, if you are coming from a different field. In our basic section we have courses and links to free external resources that help you gain that knowledge.

      Can I earn course certificates?

      Yes, you can earn course certificates for all the courses in the academy. We also provide a Associate Data Engineer certification to help you prove that you are job ready.

      Is there a monthly payment option?

      You can currently choose between a one time payment or three monthly payments.
      With the three month payment option you can split the membership fee into three small payment.

      How does the money back guarantee work?

      We are absolutely confident that you like what you get with the academy. However, if you don't like what you get and you contact Andreas within the 30 days after the purchase to get a full refund.

      Is there a free trial available?

      No, sorry there is no trial. We have a huge collection of over 200 videos you can watch for free on YouTube.

      Here's the link: http://bit.ly/YoutubeAndreaskayy

      Or read the data engineering cookbook. It's going to help you a lot learning more about Data Engineering.

      Where can I get even more information?

      If you have specific questions regarding Learn Data Engineering, the academy or the coaching, please feel free to contact Andreas directly.