According to Harvard Business Review, the role of professionals specialized in data is essential in both large and small and medium-sized companies since they are professionals with knowledge of data science, business, statistics, mathematics, and computer science. To succeed in the field of data engineering, you need to learn the essentials of the business and the basic as well as advanced concepts of the topic. It can be a good idea to pick some online data engineering courses, available from the top online course providers like Coursera, Udemy, edX, etc. Here we have listed some of the top data engineering courses from these platforms to help you gain a competitive advantage in your career.

These courses address different topics, but all of them are fundamental for a data engineer to learn and develop the necessary skills for their job. With them, you can go from knowing nothing about data engineering, data science, or data infrastructure to being able to implement complete solutions that include all the necessary components.

Major Topics Covered in Data Engineering Courses

  1. Dataflow
  2. Machine Learning
  3. Dataprep
  4. BigTable
  5. Apache Hadoop ecosystem
  6. Natural Language API
  7. Data Normalization
  8. Data Modeling
  9. Data Cleaning
  10. Data Accessibility
  11. BigQuery

Top Data Engineering Courses

Below are some of the top data engineering courses from the best online learning platforms –

Data Engineering Foundations Specialization on Coursera

Course Description

Data Engineering Foundations Specialization comprises 5 online courses covering data engineering ecosystem and lifecycle, Python, SQL, and Relational Databases. These courses are inclusive of engaging videos and hands-on practice using real tools and real-world databases.

Course Details

Duration – 5 Months

Skill Level – Beginner

Course Contents

  • Course 1 – Introduction to Data Engineering
  • Course 2 – Python for Data Science, AI & Development
  • Course 3 – Python Project for Data Engineering
  • Course 4 – Introduction to Relational Databases (RDBMS)
  • Course 5 – Databases and SQL for Data Science with Python

Data Engineering Professional Certificate by IBM on Coursera

Course Description

Data Engineering Professional Certificate can be helpful for entry-level data engineer positions. The course will give you hands-on training on the tools, databases, and concepts of data engineering design, deployment, and manage structured and unstructured data.

Course Details

Duration – 5 Months

Skill Level – Beginner

Course Contents

  • Course 1 – Introduction to Data Engineering
  • Course 2 – Python for Data Science, AI & Development
  • Course 3 – Python Project for Data Engineering
  • Course 4 – Introduction to Relational Databases (RDBMS)
  • Course 5 – Databases and SQL for Data Science with Python
  • Course 6 – Introduction to NoSQL Databases
  • Course 7 – Introduction to Big Data with Spark and Hadoop
  • Course 8 – Data Engineering and Machine Learning using Spark
  • Course 9 – Hands-on Introduction to Linux Commands and Shell Scripting
  • Course 10 – Relational Database Administration (DBA)
  • Course 11 – ETL and Data Pipelines with Shell, Airflow, and Kafka
  • Course 12 – Getting Started with Data Warehousing and BI Analytics
  • Course 13 – Data Engineering Capstone Project

Microsoft Azure for Data Engineering on Coursera

Course Description

Microsoft Azure for Data Engineering is a specialized course that prepares you for Microsoft Certified: Azure Data Engineer Associate certification, This course will help you gain expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services.

Course Details

Duration – 6 Hours

Skill Level – Intermediate

Course Contents

  • The evolving world of data and the data engineer
  • Services on the Microsoft Azure Data platform
  • Practice Exam on Store Data in Microsoft Azure

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

Course Description

Data Engineering, Big Data, and Machine Learning on GCP Specialization helps you learn the skills required to crack the industry-recognized Google Cloud Professional Data Engineer certification exam.

Course Details

Duration – 3 Months

Skill Level – Intermediate

Course Contents

  • Course 1 – Google Cloud Big Data and Machine Learning Fundamentals
  • Course 2 – Modernizing Data Lakes and Data Warehouses with GCP
  • Course 3 – Building Batch Data Pipelines on GCP
  • Course 4 – Building Resilient Streaming Analytics Systems on GCP
  • Course 5 – Smart Analytics, Machine Learning, and AI on GCP

Professional Certificate in Data Engineering Fundamentals by IBM on edX

Course Description

In the Professional Certificate in Data Engineering Fundamentals, you will learn the core principles of the data engineering ecosystem, data integration pipelines, data repositories, business intelligence, and reporting tools. The course further explores the concepts of data repositories, such as relational and non-relational databases, data warehouses, data marts, data lakes, and big data stores, etc.

Course Details

Duration – 5 Months

Skill Level – Intermediate

Course Contents

  • Course 1 – Data Engineering Basics for Everyone
  • Course 2 – Python Basics for Data Science
  • Course 3 – Python for Data Engineering Project
  • Course 4 – Relational Database Basics
  • Course 5 – SQL for Data Science
  • Course 6 – SQL Concepts for Data Engineers

Data Engineering Essentials Hands-on – SQL, Python and Spark on Udemy

Course Description

The Data Engineering Essentials Hands-on – SQL, Python and Spark course covers the key concepts of data engineering, including SQL, Programming using Python and Spark.

Course Details

Duration – 46 Hours

Skill Level – Expert

Course Contents

  • Data Engineering Labs – Python and SQL
  • Database Essentials – SQL using Postgres
  • Programming Essentials using Python
  • Setting up Single Node Data Engineering Cluster for Practice
  • Master required Hadoop Skills to build Data Engineering Applications
  • Data Engineering using Spark SQL
  • Getting Started with Spark SQL
  • Data Engineering using Spark Data Frame APIs
  • Basic Transformations – Filtering, Aggregations, and Sorting

Cloud Data Engineering on Coursera

Course Description

Cloud Data Engineering is a perfect course for beginners as well as intermediate students looking forward to using cloud computing techniques in data science, machine learning, and data engineering. The course mainly helps you to develop Data Engineering applications and use software development best practices to create easy and then complex data engineering applications.

Course Details

Duration – 4 Weeks

Skill Level – Intermediate

Course Contents

  • Getting Started with Cloud Data Engineering
  • Examining Principles of Data Engineering
  • Building Data Engineering Pipelines
  • Applying Key Data Engineering Tasks

SQL Concepts for Data Engineers on edX

Course Description

SQL Concepts for Data Engineers is a course specially designed for Data Engineers. It covers the additional SQL techniques like creating and using views to simplify and control access to underlying tables, writing and running stored procedures, and using various types of joins to accurately retrieve related data from multiple tables.

Course Details

Duration – 1 Week

Skill Level – Intermediate

Course Contents

Module 1 – Additional SQL

  • Using Views
  • Stored Procedures
  • Transactions
  • JOINs

Python for Data Engineering Project on edX

Course Description

The Python for Data Engineering Project by IBM focuses on giving a concrete understanding of data engineering to the course takers. You will learn –

  • Web scraping and data extraction using APIs Transforming data into specific data types
  • Logging operations and preparing data for loading
  • Working with Jupyter notebooks and IBM Watson Studio

Course Details

Duration – 1 Week

Skill Level – Intermediate

Course Contents

  • Collect data using APIs and Web scraping
  • Extract data from different file formats
  • Transform data and prepare for loading
  • Log data operations
  • Share your Jupyter notebook in Watson Studio
  • Submit work and review your peers

Conclusion

These data engineering courses can give you a solid ground to start with. You can, later on, start implementing your knowledge in data engineering projects and get real experience. The job market for skilled data engineers and data scientists is on an all-time high and it can be a good idea to learn data engineering and pave the way for a successful career ahead in the long run.

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