Data engineering is crucial in today’s digital landscape as organizations increasingly rely on data-driven insights for decision-making. Learning data engineering ensures proficiency in designing robust data pipelines, optimizing data storage, and ensuring data quality. This skill is essential for efficiently managing and extracting value from large volumes of data, enabling businesses to stay competitive and innovative in their industries.
This article lists the top data engineering courses that provide comprehensive training in building scalable data solutions, mastering ETL processes, and leveraging advanced technologies like Apache Spark and cloud platforms to meet modern data challenges effectively.
Data Engineering Foundations Specialization
This IBM Specialization in data engineering covers fundamental skills like Python, SQL, and Relational Databases through self-paced online courses and hands-on projects. No prior experience is needed, and you’ll gain practical knowledge using real-world tools and databases.
IBM Data Engineering Professional Certificate
This course by IBM prepares you for a career in data engineering, teaching Python, SQL, databases, and ETL processes through hands-on labs and projects. You’ll earn a Professional Certificate and gain practical experience with tools like Apache Spark and NoSQL databases, plus career support to help you land a job.
IBM Data Warehouse Engineer Professional Certificate
This course prepares you for entry-level BI or Data Warehousing Engineering roles by teaching essential skills in RDBMS, SQL, Linux/UNIX scripting, and data pipeline tools like Apache Airflow and Kafka. You’ll design, deploy, and manage data warehouses and use BI tools for analysis.
Data Engineering with AWS
This course teaches data engineering with AWS, covering data modeling, cloud data warehouses, data lakes with Spark, and automating data pipelines with Airflow. You’ll work on real-world projects, gaining hands-on experience with tools like PostgreSQL, Cassandra, and Redshift. By the end, you’ll have the skills to design, build, and manage data solutions on AWS.
Meta Database Engineer Professional Certificate
This course by Meta teaches database engineering skills using SQL, Python, and Django. You’ll learn to create, manage, and manipulate databases, develop database-driven applications, and prepare for technical interviews. Hands-on projects include database normalization, SQL automation, Python applications, and advanced data modeling.
Google Cloud Database Engineer Specialization
This course prepares you for a Database Engineer role by teaching you to design, manage, and troubleshoot databases using Google Cloud technologies. You’ll gain hands-on experience with Cloud SQL, Cloud Spanner, and Bigtable through Qwiklabs. The learning path includes on-demand courses, labs, and skill badges to build practical, real-world skills.
Microsoft Azure Data Engineering Associate (DP-203) Professional Certificate
This course prepares data engineers and developers for the DP-203 Exam: Data Engineering on Microsoft Azure. It covers designing and implementing data solutions using Azure services, integrating and transforming data, and working hands-on in a sandbox environment.
Python, Bash and SQL Essentials for Data Engineering Specialization
This course teaches essential data engineering skills in Python, Bash, and SQL, led by professional data engineers. You’ll practice with real-world applications through integrated lab exercises and create demo videos and GitHub repositories for your portfolio.
Data Engineering with Microsoft Azure
This course teaches advanced data engineering on Microsoft Azure, covering data modeling, cloud data warehouses, data lakes, and creating data pipelines using tools like Azure Synapse Analytics, Azure Databricks, and Azure Data Factory. You’ll work on real-world projects, gaining hands-on experience with large datasets and various Azure services. By the end, you’ll be equipped to design and manage complex data solutions on the Azure platform.
Data Engineering
This course teaches data engineering for data scientists, covering ETL, NLP, and machine learning pipelines using tools like Scikit-Learn. You will work on a project to build a machine-learning pipeline for categorizing emergency messages.
ASUx: Data Engineering
This course teaches SQL for interacting with databases, covering database structure, data joining, reporting queries, and script building. It features interactive videos and a capstone project for hands-on practice.
AI: Advanced Data Engineering
This advanced course teaches scalable data engineering with tools like Celery, Airflow, and graph databases, focusing on handling massive datasets and optimizing performance. Ideal for experienced data professionals, it includes hands-on projects for practical experience. The course covers creating data pipelines, managing data processing, and using various databases for large-scale data storage.
Data Engineering with Databricks
This course covers modern data engineering on Databricks’ Lakehouse platform, focusing on ETL pipelines, data transformations with Apache Spark, and Delta Lake management. Key skills include managing Databricks clusters, SQL and DataFrame operations, and production-ready pipelines with Delta Live Tables.
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