9 Best Data Engineering Courses

In today's data-driven world, data engineering plays a vital role in transforming raw data into meaningful insights. As organizations strive to leverage the power of data, the demand for skilled data engineers continues to soar. If you're eager to embark on a rewarding career in data engineering or enhance your existing skills, choosing the right courses and certifications is essential.

This comprehensive guide will unveil the best data engineering courses and certifications available today. This resource is designed to help you navigate the vast landscape of data engineering education, enabling you to select the most valuable and reputable options to accelerate your career growth.

Investing in the best data engineering courses and certifications, you'll gain the knowledge, skills, and industry recognition necessary to excel in the field. These resources will empower you to design scalable data solutions, optimize data workflows, and contribute to data-driven decision-making within organizations.

Top Data Engineering Courses List

Data Engineering on the Google Cloud platform
Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Preparing for the Google Cloud Professional Data Engineer Exam
Advance Your Data Engineering Skills
Data Engineer Online Hands-On Courses – Dataquest
Data Engineering

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1. Data Engineering on the Google Cloud platform

With Google Cloud Platform (GCP) rapidly gaining popularity and many companies migrating their infrastructure to GCP, this course offers the most practical solutions for real-world data engineering use cases on the cloud. Designed to encompass the end-to-end lifecycle of a typical big data ETL project, both in batch processing and real-time streaming and analytics, this course equips you with essential skills for data engineering on GCP.

Course rating: 4.6 out of 5.0 (464 Rating total)
Duration: 10 Hours
Certificate: Certificate of completion

With this data engineering course, you will:

Pyspark for ETL/Batch Processing on GCP using Bigquery as a data warehousing component.
Automate and orchestrate SparkSql batch jobs using Apache Airflow and Google Workflows.
Sqoop for Data ingestion from CloudSql and using Airflow to automate the batch ETL.
Difference between Event-time data transformations and process-time transformations
Pyspark Structured Streaming - Real-Time Data streaming and transformations.
Save real-time streaming raw data as external hive tables on Dataproc and perform ad-hoc queries using HiveSql.
Run Hive-SparkSql jobs on Dataproc and automate micro-batching and transformations using Airflow.
Pyspark Structured Streaming - Handling Late Data using watermarking and Event-time data processing.
Using different file formats - AVRO and Parquet. Different scenarios in which to use the file formats.

The course focuses on the key components of batch processing and streaming jobs, providing comprehensive coverage of each aspect. You'll start by learning how to write ETL jobs from scratch using Pyspark, a powerful data processing framework. You'll explore the storage components on GCP, including Google Cloud Storage (GCS) and Dataproc HDFS, to efficiently handle and store your data.

Loading data into a data warehousing tool is a crucial aspect of data engineering, and this course guides you through using BigQuery on GCP for seamless data ingestion and analysis. Data orchestration and managing dependencies are essential in any data engineering project, and you'll learn how to handle and write data orchestration workflows using Apache Airflow (Google Composer) in Python.

Batch data ingestion is a common requirement, and this course covers the usage of Sqoop, CloudSql, and Apache Airflow for efficient data loading. Real-time data streaming and analytics are becoming increasingly important, and you'll dive into the latest APIs and technologies, including Spark Structured Streaming with Python, to process and analyze streaming data in real-time.

Additionally, you'll explore micro-batching techniques using PySpark streaming and Hive on Dataproc, enabling you to handle large volumes of data efficiently.

By the end of this course, you'll have mastered practical data engineering on the Google Cloud Platform. You'll be equipped with the skills to design, develop, and deploy batch processing and real-time streaming solutions, leveraging the full potential of GCP's data engineering ecosystem.

2. Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

Learn Data Engineering Courses with GCP Professional Certificate from Google Cloud. This program provides the skills you need to advance your career in data engineering and provides a pathway to earn the industry-recognized Google Cloud Professional Data.

Course rating: 78,017 total enrollments
Duration: 5 months (3 hours/week)
Certificate: Certificate of completion

With this data engineering course, you will:

Learn the skills needed to be successful in a data engineer role
Prepare for the Professional Data Engineer certification
Learn about the infrastructure and platform services provided by Google Cloud Platform

This program provides the skills you need to advance your career in data engineering and provides a pathway to earn the industry-recognized Google Cloud Professional Data Engineer certification. Through a combination of presentations, demos, and labs, you'll enable data-driven decision-making by collecting, transforming, and publishing data; and you'll gain real-world experience through a number of hands-on Qwiklabs projects that you can share with potential employers.

You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and operationalizing machine-learning models. For learners looking to get certified, this program will also provide sample questions similar to those on the exam, including solutions and practice exam quizzes that simulate the exam-taking experience.

Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers. If you'd like to earn your Google Cloud certification, you will need to register for and pass the certification exam. Please note that this program helps equip you with the skills you need to take the certification exam, but the certification and certification fee is not included in the cost of this training program.

You can take Data Engineering with GCP Professional Certificate Certificate Course on Coursera.

3. Preparing for the Google Cloud Professional Data Engineering Exam

Learn Preparing for the Google Cloud Professional Data Engineering Exam from Google Cloud. From the course: "The best way to prepare for the exam is to be competent in the skills required for the job." This course uses a top-down approach.

Course rating: 4.6 out of 5.0 (965 Rating total)
Duration: 8 Hours
Certificate: Certificate of completion

With this data engineering course, you will:

Review each section of the exam using the highest-level concepts to identify what is already known and surface gap areas for study.
Practice case study analysis and solution proposal methods and thinking skills.
Learn information, tips, and general advice about how to prepare for the exam.
Integrate prior technical skills into practical skills for the job role. Help you become a Data Engineer.

This data engineering course uses a top-down approach to recognize knowledge and skills already known and to surface information and skill areas for additional preparation. You can use this course to help create your own custom preparation plan. It helps you distinguish what you know from what you don't know. And it helps you develop and practice the skills required of practitioners who perform this job.

This data engineering course follows the organization of the Exam Guide outline, presenting highest-level concepts, "touchstones", for you to determine whether you feel confident about your knowledge of that area and its dependent concepts, or if you want more study. You also will learn about and have the opportunity to practice key job skills, including cognitive skills such as case analysis, identifying technical watchpoints, and developing proposed solutions.

These are job skills that are also exam skills. You will also test your basic abilities with Activity Tracking Challenge Labs. You will have many sample questions similar to those on the exam, including solutions. The end of the course contains an ungraded practice exam quiz, followed by a graded practice exam quiz that simulates the exam-taking experience.

You can take Preparing for the Google Cloud Professional Data Engineer Exam Certificate Course on Coursera.

4. Advance Your Data Engineering Skills

Build extensive data engineering and DevOps skills as you learn essential concepts. With this learning path, master the tools of the trade and how to apply them in real-world data project environments and platforms.

With this data engineering course, you will:

Build a foundation in data engineering and data science DevOps.
Explore techniques deployed in common tools and platforms.
Develop deeper skills in data science application programming.

This data engineering course includes Data science expert Ben Sullins explains the basics of big data and demonstrates how to perform core data engineering tasks including staging, profiling, cleansing, and migrating data, exploring the possibilities NoSQL databases offer developers for unparalleled flexibility and performance, learn the basics of HBase.

The Hadoop data for big data analytics, get an understanding of the HBase architecture and basic read/write commands, discover how to make Apache, spark work with other big data technologies to build data pipelines for data engineering and DevOps, learn about use cases and best practices for architecting batch mode applications using big data technologies such as Hive and Apache Spark, learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark, get the data you need for analysis and reporting by writing your own SQL code.

Learn how to write basic SQL queries, sort and filter data, and join results from different tables and data sets, explore the fundamentals of NoSQL, learn the differences between NoSQL and traditional relational databases, discover how to perform common data science tasks with NoSQL, and more, get Ben Sullins's 12 must-have SQL techniques for data science pros—engineers, DevOps, data miners, programmers, and other systems specialists, learn how to choose a NoSQL database solution that's right for your organization, including options that work with Microsoft SQL Server and on the cloud, you can take Become a Data Engineer: Mastering the Concepts Course on LinkedIn Learning.

You can take Become a Data Engineering course: Mastering the Concepts Certificate Course on LinkedIn Learning.

5. Data Engineering Online Hands-On Courses – Dataquest

Learn how to build data pipelines to work with large data sets.

With this data engineering course, you will:

How to work with production data
Key computer science concepts like data structures, algorithms, and recursion
How to handle larger data sets

This path teaches you how to utilize Python along with pandas to work with large data sets and load them into Postgres data. In this path, you'll learn how to work with big data, build data pipelines, and more.

You can take Data Engineer Online Hands-On Courses – Dataquest Certificate Course on Dataquest.

6. Data Engineering

Break into a career in Data Engineering with this step-by-step path. Learn to design, build, and maintain big data pipelines for data-driven applications.

With this data engineering course, you will:

Design, build, and maintain big data pipelines for data-driven applications.
Learn Hadoop, Spark, software engineering, and cloud computing.
Drive business value through data warehouse design, SQL database systems, and integrating ETL and business intelligence tools.
Build scalable data pipelines by enhancing your data toolkit with functional programming in Scala and parallel computing.
Explore how to design, build, and deploy machine learning systems on the Google Cloud Platform, using a production environment to develop an application.

This data engineering course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. This database engineering course has no prerequisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. This course will cover Chapters 1-5 of the textbook “Python for Everybody”. Once a student completes this course, they will be ready to take more advanced programming courses. This database engineering course covers Python 3.

You can take Become a Data Engineer Certificate Course on Coursera.

Thank you for reading this. We hope our course curation would help you to pick the right course to learn data engineering. If you have made it this far then certainly you are willing to learn more and here at Coursesity, it is our duty to enlighten people with knowledge on topics they are willing to learn. Here are some more topics that we think will be interesting for you!