Data engineering is a dynamic field at the forefront of the data-driven revolution. With the ever-increasing volume of data generated in today's digital age, data engineers play a crucial role in collecting, processing, and transforming data into valuable insights. If you're looking to kickstart your career in data engineering, it's essential to begin with a strong foundation.

Fortunately, there are plenty of online courses designed specifically for beginners. Here, we've curated a list of the top 10 data engineering courses to kickstart your journey into this exciting field.

1. Data Engineering - Beginner Module by Data2Bots Academy

The Data Engineering - Beginner Module by Data2Bots Academy takes the top spot on our list. This comprehensive course is designed to transform aspiring data engineers into young professionals in the field. The curriculum begins with a strong focus on building foundational skills, covering topics such as Python programming, SQL, version control, and test-driven development.

One of the standout features of this course is its hands-on approach. Students are exposed to real-world scenarios and practical exercises that reinforce their learning. Aspiring data engineers also delve into the intricacies of designing, building, and maintaining scalable and reliable data pipelines. The course covers both open-source tools and AWS-specific services, providing students with a well-rounded understanding of industry-standard technologies.

Duration: 3 Months

2. DataCamp Data Engineer Career Track

This track will teach you everything you need to know to become a data engineer by teaching you Python, SQL, and Git from the ground up. You'll learn how to query, input, and modify data in relational databases and gain hands-on experience importing and cleaning data in Python, optimizing your code for efficiency, and writing tests to validate your code.

Throughout this track, you'll learn some of the most important data engineering tools, beginning with SQL and Python and progressing to cloud computing, data clearing, and working with Git. These fundamental skills will enable you to work with data in various ways, allowing you to gain the knowledge required to become a data engineer.

You'll also learn the fundamental concepts and skills data engineers need, such as interpreting data visualizations, writing functions, and using version control.  By the end of this track, you'll have the tools and knowledge you need to advance your career by handling common data engineering duties.

Duration: 57 hours

3. Data Engineering with Databricks

This comprehensive introduction to the components of the Databricks Lakehouse Platform that directly support putting ETL pipelines into production will benefit data professionals from all walks of life. You will use SQL and Python to define and schedule pipelines that incrementally process new data from various data sources to power Lakehouse analytic applications and dashboards.

This course teaches Databricks Data Science & Engineering Workspace, Databricks SQL, Delta Live Tables, Databricks Repos, Databricks Task Orchestration, and the Unity Catalogue through hands-on exercises.

Duration: 2 full days or 4 half days

4. Udacity Data Engineer Nanodegree

Students enrolled in the Data Engineer Nanodegree Programme will gain the technical skills required to work as a data engineer. Students will complete four courses and five projects as part of this program. Students will take on the role of a data engineer at a music streaming company throughout the projects. In each project, they will work with the same type of data but with increasing data volume, velocity, and complexity.

The program will take approximately five months if students spend 5-10 hours per week in the classroom. The program costs $999, including access to Udacity's services. The need for data engineers has never been greater. The combination of a world-class curriculum and excellent services provided by the Udacity Data Engineer Nanodegree program is the ideal way to enter this exciting field.

Duration: 5 months

5. Data Engineering Fundamentals by IBM & edX

This six-course IBM Professional Certificate is an excellent starting point for those interested in a career in data engineering. You will learn the fundamentals of data engineering and have the opportunity to put your knowledge to use in hands-on labs. You'll learn about the data engineering ecosystem, data integration pipelines, data repositories, Business Intelligence, and Reporting tools.

Data repositories such as relational and non-relational databases, data warehouses, data marts, data lakes, and big data stores will be covered, as well as how to store and process this data. The certificate begins with an introductory course, then moves on to how Python is used by Data Scientists in Artificial Intelligence and Development, and allows you to create a Python project to put these skills into practice. After that, the certificate covers relational databases and SQL.

Duration: 4 months

6. Data Engineering in AWS by Coursera

The first AWS Certified Machine Learning Specialty specialization course is Data Engineering in AWS. This course teaches students how to analyze various data collection techniques. They will also learn how to deal with missing data. This course is divided into two modules, each of which is further subdivided into Lessons and Video Lectures.

This course provides approximately 2:30-3:00 hours of video lectures that provide learners with both theory and hands-on knowledge. In addition, each module includes a graded and ungraded quiz to assess learners' abilities.

Duration: 3hrs

7. Google Cloud Platform Big Data and Machine Learning Fundamentals

This course introduces participants to Google Cloud's big data capabilities. Participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities through a combination of presentations, demos, and hands-on labs. This course demonstrates the simplicity, adaptability, and power of big data solutions on Google Cloud. This course introduces participants to Google Cloud's big data capabilities.

Participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities through a combination of presentations, demos, and hands-on labs. This course demonstrates the simplicity, adaptability, and power of big data solutions on Google Cloud.

Duration: 4hrs

Conclusion

These top 10 data engineering courses for beginners offer a diverse range of options to kickstart your career in data engineering. Whether you're interested in cloud platforms like AWS and GCP or prefer open-source tools like Apache Kafka and Hadoop, there's a course here to suit your needs. So, roll up your sleeves, start learning, and embark on an exciting journey into the world of data engineering.

Remember that success in data engineering requires theoretical knowledge and practical skills. As you explore these courses, be sure to practice what you learn by working on personal projects or contributing to open-source data engineering projects. Building a strong portfolio of projects will set you apart when you enter the job market.