Are you looking for the Best Data Engineering Courses Coursera? If yes, then this article is for you. In this article, I will share the 7 Best Data Engineering Courses Coursera.
So, give a few minutes to this article and find out the Best Data Engineering Courses Coursera for you.
Now, without further ado, let’s get started-
Best Data Engineering Courses Coursera
- 1. Data Engineering Foundations Specialization
- 2. Data Engineering, Big Data, and Machine Learning on GCP Specialization
- 3. Python, Bash, and SQL Essentials for Data Engineering Specialization
- 4. Google Cloud Database Engineer Specialization
- 5. Data Warehousing for Business Intelligence Specialization
- 6. Microsoft Azure for Data Engineering
- 7. Introduction to Data Engineering
- Summary of Best Data Engineering Courses Coursera
- Conclusion
1. Data Engineering Foundations Specialization
Rating- 4.6/5
Time to Complete- 3-6 months
Best For- Beginner
In the Data Engineering Foundations specialization by IBM, you’ll learn the basics of handling data in five easy courses. These courses are designed for beginners, so you don’t need any prior experience.
Throughout the specialization, you’ll learn about how data works and how to use programs like Python and SQL to work with it. The lessons are taught with fun videos, and you’ll get to practice what you’ve learned with real data and tools.
By the end, you’ll be able to do things like organize data, analyze it, and use different software to work with it. You’ll also work on some projects to test your skills. So, if you’re curious about data and want to learn how to work with it, this specialization is a great place to start.
Best For-
- Those who are beginners.
Interested in Enroll?
If yes, then check it out here- Data Engineering Foundations Specialization
2. Data Engineering, Big Data, and Machine Learning on GCP Specialization
Rating- 4.6/5
Time to Complete- 3-6 months
Best For- Intermediate
Did you know that when you get certified in Google Cloud, most people feel more confident in their skills? This program helps you get ready for the Google Cloud Professional Data Engineer certification, which companies really respect.
Here’s what you’ll do:
First, take the Coursera Data Engineering Professional Certificate. It teaches you everything about data engineering.
Then, check out other things that can help you get ready for the certification exam.
After that, read the Professional Data Engineer Exam Guide to know what the exam will be like.
Practice answering questions with Professional Data Engineer Sample Questions.
Finally, sign up for the Google Cloud Certification Exam. You can take the exam online or at a test center.
In this program, you’ll do hands-on labs using the Qwiklabs platform. These labs help you practice what you learn in the videos. You’ll work on projects using Google Cloud products like BigQuery. These projects help you get real experience with the things you learn in the courses.
Best For-
- Those who have Intermediate level knowledge of Python & SQL.
Interested in Enroll?
If yes, then check it out here- Data Engineering, Big Data, and Machine Learning on GCP Specialization
3. Python, Bash, and SQL Essentials for Data Engineering Specialization
Rating- 4.5/5
Time to Complete- 3-6 months
Best For- Beginners
If you want to become a data engineer, the Python, Bash, and SQL Essentials for Data Engineering Specialization is a good starting point. In today’s world, everything we do generates big data, and businesses use this data to make decisions. Data engineers are the ones who collect, clean, and manage this data.
To become a data engineer, you need to be skilled in Python, Bash, and SQL. This specialization gives you a basic understanding of these skills. Led by professional data engineers, the courses are easy to follow and include practice exercises. You can apply what you learn in your work or studies right away.
Each course includes practice exercises using tools like Visual Studio Code or Jupyter notebooks. You’ll work on real-world projects to practice your Python, Bash, and SQL skills. You’ll also create demo videos and a GitHub repository to showcase your work to potential employers. By the end of the specialization, you’ll have the basic skills needed to start working on more complex data engineering projects.
Best For-
- Those who have beginner-level Linux skills.
Interested in Enroll?
If yes, then check it out here- Python, Bash, and SQL Essentials for Data Engineering Specialization
4. Google Cloud Database Engineer Specialization
Rating- 4.7/5
Time to Complete- 3-6 months
Best For- Intermediate
If you want to become a Database Engineer, this specialization is for you. A Database Engineer works with databases used by applications to store and retrieve data. This learning path includes a series of on-demand courses, labs, and skill badges that give you hands-on experience with Google Cloud technologies used in the role. After completing the path, you can explore our catalog with over 700 labs and courses to continue your professional development.
In this specialization, you’ll do labs using our Qwiklabs platform. These labs help you practice what you learn in the video modules. You’ll also learn about and work with Google Cloud databases like Cloud SQL, Cloud Spanner, and Bigtable. Gain practical experience and skills to excel as a Database Engineer.
Best For-
- Those who have previous experience with database development using SQL, general programming skills, and an understanding of relational and NoSQL database design.
Interested in Enroll?
If yes, then check it out here- Google Cloud Database Engineer Specialization
5. Data Warehousing for Business Intelligence Specialization
Rating- 4.5/5
Time to Complete- 3-6 months
Best For- Advanced
In this specialization, you’ll learn how to meet business needs by designing data warehouses and visualizing data using dashboards and visual analytics. These skills are important in many technology fields.
You’ll start by learning about structured data modeling and practicing SQL coding. Then, you’ll dive into data warehouse design and manipulation, working with large datasets in a real-world environment.
Using MicroStrategy, a top BI tool, you’ll create dashboards and visual analytics. You’ll also use OLAP and Visual Insights to analyze data.
In the final Capstone Project, you’ll put your skills to use by building a basic data warehouse, adding data to it, and creating dashboards and visualizations to share with others. It’s a hands-on way to learn and apply your knowledge.
Best For-
- Those who have some prior experience with software engineering and business intelligence.
Interested in Enroll?
If yes, then check it out here- Data Warehousing for Business Intelligence Specialization
6. Microsoft Azure for Data Engineering
Rating- 4.5/5
Time to Complete- 1-4 weeks
Best For- Intermediate
In this course, you’ll explore the changing world of data and how cloud technologies, like Microsoft Azure, are opening up new possibilities for businesses. As a Data Engineer, you’ll learn how to leverage these technologies to benefit organizations.
This course is part of a larger specialization aimed at Data engineers and developers who want to showcase their skills in designing and implementing data solutions using Microsoft Azure data services. It’s also helpful for those preparing for the Exam DP-203: Data Engineering on Microsoft Azure (beta).
This is the first course in a series of 10 courses designed to prepare you for the exam. Through these courses, you’ll gain expertise in integrating, transforming, and consolidating data from different sources into structures suitable for building analytics solutions using Microsoft Azure data services. Each course covers the concepts and skills tested in the exam.
By the end of the specialization, you’ll be ready to take Exam DP-203: Data Engineering on Microsoft Azure (beta) and demonstrate your knowledge and skills in data engineering on the Azure platform.
Best For-
- Those who have a solid knowledge of data processing languages, such as SQL, Python, or Scala, and an understanding of parallel processing and data architecture patterns.
Interested in Enroll?
If yes, then check it out here- Microsoft Azure for Data Engineering
7. Introduction to Data Engineering
Rating- 4.7/5
Time to Complete- 1-4 weeks
Best For- Beginners
This course introduces you to the core concepts, processes, and tools essential for a foundational understanding of data engineering. You’ll explore the data engineering ecosystem, learn about various data repositories and processing tools, and understand the typical data engineering lifecycle.
Additionally, you’ll discover career opportunities in Data Engineering and hear from experienced professionals. Through hands-on labs, you’ll work with relational databases, loading data, and performing basic queries.
Best For-
- Those who have Intermediate level knowledge of Python & SQL.
Interested in Enroll?
If yes, then check it out here- Introduction to Data Engineering
Summary of Best Data Engineering Courses Coursera
| S/N | Course Title | Description |
|---|---|---|
| 1 | Data Engineering Foundations Specialization | Teaches basic skills for data engineering, like how to design data systems and use Python and SQL. |
| 2 | Data Engineering, Big Data, and Machine Learning on GCP Specialization | Shows how to work with big data and machine learning on Google Cloud Platform (GCP). |
| 3 | Python, Bash, and SQL Essentials for Data Engineering Specialization | Introduces key skills in Python, Bash, and SQL for data tasks. |
| 4 | Google Cloud Database Engineer Specialization | Helps you learn to create data solutions using Google Cloud services. |
| 5 | Data Warehousing for Business Intelligence Specialization | Explains how to organize and analyze data for business decisions. |
| 6 | Microsoft Azure for Data Engineering | Gets you ready for a Microsoft exam on designing data solutions. |
| 7 | Introduction to Data Engineering | Gives a basic understanding of data engineering and its tools. |
Conclusion
In this article, I tried to cover all the Best Data Engineering Courses Coursera. If you have any doubts or questions, feel free to ask me in the comment section.
All the Best!
Enjoy Learning!
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Written By Aqsa Zafar
Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.