6 Best Online Data Engineering Courses & Certification

Students with so many Data Engineering courses find it extremely difficult to meet their needs. Learners often ask if there is a Data Engineering course for each case. The response is YES. Below are popular courses available. Registering for the right course is an important factor in your career progression. In this article, the best Data Engineering courses were selected by experts in 2023.

The main aim is to illustrate the best known courses in every category.

Data Engineering Courses

Select one that best suits your needs, based on your preference.

However, let’s look at the best Data Engineering courses on the market.

1. Become a Data Engineer Certification (Coursera)

Duration: Self-paced

Rating: 4.6 out of 5

If you are seeking guidance and expertise to start your career as a data engineer, then it is one of the top online options. There is no experience to start your learning and you can follow a step-by – step plan based on relevant suggestions. Using the tutorials and hands-on projects to work on your skills and you are ready to apply for your dream job by the end of the journey.

Key Highlights:

  • The lectures can be obtained on and at any time on any device.
  • Talk to your peers through the forums and share thoughts and doubts.
  • Work on projects in real life and add them to your portfolio which can be discussed during job interviews.
  • Building data models, database systems and using business intelligence tools improve the business value of your company.
  • Use ML frameworks to build a solution on Google Cloud Platform.

You can Sign up Here 

2. Data Engineering Nanodegree Certification (Udacity)

Duration: 5 months, 5 hours per week

Rating: 4.5 out of 5

With the exponential rise of the rate of data growth nowadays, engineering data is becoming increasingly important and useful information is extracted from it. This nanodegree is designed to help you learn about techniques for designing a data model, building stored storage, processing automation and handling various information scales. To study and follow easily, you need to have medium-sized knowledge of Python and SQL. Start the lesson with a capstone project to show what you learned in the lectures.

Key Highlights:

  • Explore how and how cloud-based warehouses are built.
  • To build databases and templates, use NoSQL, PostgreSQL and Apache Cassandra.
  • Plan and automate pipelines for optimization and monitor progress.
  • Get to know Apache Spark and learn how to use massive datasets.
  • The apprenticeship is tailored to meet your personal objectives.
  • Connect on one technical mentor with your person to explain your doubts and get guidance.
  • Access to meetings which will prepare you for interviews, enhance your resume and more.

You can Sign up Here

3. Data Engineering with Google Cloud (Coursera)

Duration: Self-paced

Rating: 4.7 out of 5

This specialized certification program helps you gain the basics you need in data engineering to develop your career. You will receive additional training in this program to prepare you for the certification of Google Cloud Professional Data Engineer. The curriculum provides a mix of lectures, demonstrations and laboratories that allow you to better understand the key concepts. During the program, you can make data-driven decisions by collecting, transforming, publishing and gaining real-world expertise through a variety of practical Qwiklab projects. You receive a certificate of completion after completing the program with the given project that can be shared with employers.

Key Highlights:

  • Give the opportunity to perform essential job skills, such as design, development and operation of data processing systems and machine learning models
  • Master the key skills that you need to become a good data engineer by covering all the main concepts
  • It comprises of 6 courses focused on enhancing the Google Cloud platform awareness such as big data, machine learning, etc.
  • Cover different tools available on Google Cloud data transformation platforms such as BigQuery, Spark on Cloud Dataproc, etc.

You can Sign up Here

4. Become a Data Engineer: Mastering the Concepts (LinkedIn Learning – Lynda)

Duration: 16 hours

Rating: 4.6 out of 5

In this way of learning, you will start exploring all the key concepts which equip you with the skills to put them into practice in the real world and pursue a career in this field. Start with the basic training which will introduce you to the necessary techniques and concepts prior to moving on to databases which can be used for the storage and management of any data scale. After these basic concepts have been finished, you can use the various tools and open-source software that show you how to design large data applications, build data pipelines, manage apps in real time using Hazelcast and Apache Spark, in order to mention a few crucial topics.

Key Highlights:

  • Introductory lectures discuss the exercises and the configurations necessary for the tools used.
  • Consider how key activities such as staging, washing, and transfer of data can be done.
  • Work on NoSQL to improve the solutions’ versatility and efficiency.
  • Learn about best practices and use cases for both saved and data streams.
  • Discover HBase and Hadoop database architecture.
  • Get free access to all content after registration for the first thirty days.
  • Readings and exercises, both online and offline.

You can Sign up Here

5. Data Engineering, Big Data on Google Cloud Platform (Coursera)

Duration: 1 month, 16 hours per week

Rating: 4.5 out of 5

This extensive Google Cloud specialization provides you with practical experience about GCP data processing systems. Individuals will know how to develop systems before proceeding with the development phase all throughout classes. In relation, you analyze structured and unstructured data, implement autoscaling and apply ML techniques for information extraction.

Key Highlights:

  • To train and predict solutions, use open source software like TensorFlow Cloud ML.
  • Design and architecture of infrastructure pipelines.
  • Once transformed, cleaned and checked, BigQuery is used for drawing insights from large datasets.
  • Besides the stored data, information is gathered from an instant data source.
  • Complete hands-on training and qualification tests.
  • You can learn at your own speed with the flexible deadline.

You can Sign up Here 

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Wrapping Up

This is the list of the 6 Best Online Data Engineering Courses & Certification of 2023. They are popular and loved by many experienced Data Engineering learners. You will find between these courses what you need to learn in order to continue your Data Engineering learning journey.

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