All Data Engineering Courses

1. Data Engineering Basics Introduction to Data Engineering Introduction to Data Engineering with over 1 hour of videos including my journey here. Andreas Kretz % COMPLETE Computer Science Fundamentals A complete guide of topics and resources you should know as a Data Engineer. Andreas Kretz % COMPLETE Introduction to Python Learn all the fundamentals of Python to start coding quick Amit Jain % COMPLETE Python for Data Engineers With this comprehensive course, you will expand your Python skill set to tackle complex Data Engineering projects with ease. Andreas Kretz % COMPLETE Data Preparation & Cleaning for Machine Learning All you need for preparing data to enable Machine Learning Andreas Kretz % COMPLETE Docker Fundamentals Learn all the fundamental Docker concepts with hands-on examples Andreas Kretz % COMPLETE SQL for Data Engineers Learn fundamentals and advanced techniques for real-world data challenges Andreas Kretz % COMPLETE Successful Job Application Everything you need to successfully apply for Data Engineering jobs Andreas Kretz % COMPLETE Becoming a Better Data Engineer Master the core principles of Data Engineering and build smarter pipelines Andreas Kretz % COMPLETE The Hidden Foundation of GenAI Learn Embeddings - The Core of Search, RAG, and LLMs Andreas Kretz % COMPLETE 2. Platform & Pipeline Design Fundamentals Data Platform And Pipeline Design Learn how to build data pipelines with templates and examples for Azure, GCP and Hadoop. Andreas Kretz % COMPLETE Platform & Pipelines Security Learn the important security fundamentals for Data Engineering Andreas Kretz % COMPLETE Choosing Data Stores Learn the different types of data stores and when to use which. Andreas Kretz % COMPLETE Data Modeling 1 Learn to create the data models for SQL, NoSQL databases and Data Warehouses Andreas Kretz % COMPLETE Data Modeling 2 - Relational Data Modeling Learn how to model your data for relational databases Andreas Kretz % COMPLETE Data Modeling 3 - Dimensional Data Modeling Learn how to model your data for analytical data stores with dimensional modeling Andreas Kretz % COMPLETE 3. Fundamental Tools Building APIs with FastAPI Learn the fundamentals of designing, creating and deploying APIs with FastAPI and Docker Andreas Kretz % COMPLETE Apache Kafka Fundamentals Learn the fundamentals of Apache Kafka Andreas Kretz % COMPLETE Apache Spark Fundamentals Apache Spark quick start course in Python with Jupyter notebooks, DataFrames, SparkSQL and RDDs. Andreas Kretz % COMPLETE Data Engineering on Databricks Everything you need to get started with Databricks. From setup to building ETL pipelines & warehousing. Andreas Kretz % COMPLETE MongoDB Fundamentals Learn how to use MongoDB Andreas Kretz % COMPLETE Log Analysis with Elasticsearch Learn how to use Elasticsearch to monitor and debug your pipelines through log indexing Andreas Kretz % COMPLETE Airflow Workflow Orchestration Learn how to orchestrate your data pipelines with Apache Airflow Andreas Kretz % COMPLETE Snowflake for Data Engineers Everything you need to get started with Snowflake Andreas Kretz % COMPLETE dbt for Data Engineers Everything you need to transform data with dbt and Snowflake Andreas Kretz % COMPLETE Apache Iceberg Fundamentals Get hands-on with Apache Iceberg and build a complete local Lakehouse setup using Spark, Docker, and MinIO. Andreas Kretz % COMPLETE DuckDB for Data Engineers: From Local to Cloud with MotherDuck Learn how to build data workflows that run on your laptop, in the cloud, or across both using DuckDB and MotherDuck. Andreas Kretz % COMPLETE Spark Declarative Pipelines & Lakeflow Designer on Databricks Learn how to move from notebook-based workflows to structured, production-ready pipelines in Databricks using a modern declarative approach. Andreas Kretz % COMPLETE High-Performance Data Analysis with Exasol Exasol is a massively parallel analytical database built for speed. This course gives you a practical, hands-on introduction to it. You'll deploy Exasol Personal on AWS, run complex analytical queries on realistic datasets, and write Python UDFs that execute custom logic directly inside the database. You'll also explore in-database ML and LLM inference, so you can apply models to your data without exporting it. By the end, you'll know where Exasol fits in a modern data architecture and how to use its core features in real analytics workflows. Andreas Kretz % COMPLETE FREE 4. Full Hands-On Example Projects Data Engineering on AWS Full 5 hours course with complete example project. Building stream and batch processing pipelines on AWS. Andreas Kretz % COMPLETE Data Engineering on Azure Ingest, Store, Process, Serve and Visualize Streams of Data by Building Streaming Data Pipelines in Azure. Kristijan Bakarić % COMPLETE Data Engineering on GCP Build a full end-to-end project will all important GCP tools. Andreas Kretz % COMPLETE Building a Lakehouse on AWS and GCP How to integrate a Data Lake with a Data Warehouse and qu