Data Engineering

Build the pipelines, warehouses and cloud infrastructure that data and AI teams depend on.

IBM Data Engineering Professional Certificate

Data Engineering Bootcamps & Certificates

A 16-course IBM program covering Python, SQL, ETL, NoSQL, Spark and data warehousing for beginners aiming at entry-level data engineering roles.

Airflow Python SQL

Data Engineer Career Track

Data Engineering Bootcamps & Certificates

A 10-course career track covering SQL, Python, Airflow, cloud, and data warehousing, ending in an accredited data engineer certificate.

Python SQL

Introduction to Data Engineering

Data Pipelines & ETL

A four-hour intermediate DataCamp course that walks through databases, parallel processing, Airflow scheduling, and building a working ETL pipeline.

Airflow Python SQL

Introduction to Apache Airflow in Python

Data Pipelines & ETL

Hands-on Apache Airflow 3 course covering Dags, scheduling, sensors, monitoring, branching, and a sales ETL pipeline project in about 4 hours.

Airflow Python

Data Engineering on AWS - The complete training

Data Pipelines & ETL

A 19-hour Udemy course mapping the four AWS Certified Data Engineer Associate (DEA-C01) exam domains, from ingestion to security and governance.

AWS Python

The Complete dbt Bootcamp: Zero to Hero + Certification Prep

Data Warehousing & Modeling

A hands-on dbt course built around an Airbnb analytics project, with theory, Snowflake setup, testing, and a practice exam for dbt certification.

dbt SQL

Data Warehousing Concepts

Data Warehousing & Modeling

A beginner-friendly DataCamp course covering data warehouse fundamentals, architecture, and schema design using real industry data.

SQL

Apache Spark with Scala - Hands On with Big Data!

Big Data & Distributed Computing

A hands-on Udemy course teaching Apache Spark with Scala through 20+ real coding examples, covering RDDs, SparkSQL, streaming, and MLlib.

Apache Spark

Data Engineering, Big Data, and Machine Learning on GCP Specialization

Cloud Data Platforms

Learn Google Cloud data engineering through four courses covering storage, batch and streaming pipelines, and practical machine learning labs.

BigQuery Google Cloud TensorFlow

Snowflake - The Complete Masterclass

Cloud Data Platforms

Learn Snowflake through guided lessons, assignments, and quizzes, with coverage spanning warehouse fundamentals and more advanced platform topics.

Snowflake SQL

Machine Learning in Production (DeepLearning.AI)

MLOps & Model Deployment

Explore production ML with Andrew Ng, covering deployment choices, error analysis, data quality, and monitoring across three focused modules.

Python TensorFlow

Ultimate DevOps to MLOps Bootcamp - Build ML CI/CD Pipelines

MLOps & Model Deployment

Build a house-price prediction pipeline with MLflow, FastAPI, Docker, and Kubernetes while learning CI/CD workflows for machine learning.

Python

Intermediate Data Importing in R

Data Pipelines & ETL

Master diverse data importing techniques in R, from databases to web sources, and enhance your data preparation skills.

Data Engineering is the infrastructure layer everything else runs on. This pillar covers ingesting data from source systems, transforming it reliably, modelling it for analysis, storing it at scale, and operating the whole thing in the cloud without surprise bills. You will find pipeline and orchestration courses built around Airflow, dbt and Kafka, dimensional modelling and warehousing, distributed processing with Spark, platform-specific tracks for AWS, Azure, Google Cloud, Snowflake and Databricks, and MLOps for teams putting models into production. Strong SQL and working Python are assumed by most material here.