Coursera IBM Data Engineering Professional Certificate Review-2025

Are you planning to enroll in Coursera IBM Data Engineering Professional Certificate Review?… If yes, first read my Coursera IBM Data Engineering Professional Certificate Review.

In this “Coursera IBM Data Engineering Professional Certificate Review“, I covered everything related to the Coursera IBM Data Engineering Professional Certificate such as the content quality, worthiness of projects, value for money or not, etc.

Now, without further ado, let’s get started-

Coursera IBM Data Engineering Professional Certificate Review

Is Coursera IBM Data Engineering Professional Certificate Worth It?

Yes, the Coursera IBM Data Engineering Professional Certificate can be a great way to learn about working with data. You can do it all online and go at your own speed. When you finish, it might help you get better jobs.

Just remember, there’s a cost to take the courses. You’ll need to keep yourself interested and motivated to learn.

To figure out if it’s right for you, think about what kind of job you want. Do you like learning online? Can you pay for it? And see if you’re starting from scratch or already know a bit.

In short, the certificate could be a good choice, but take time to decide based on what you want and how you like to learn.

Review Summary of Coursera IBM Data Engineering Professional Certificate

What People Liked	Summary
Learned a Lot	Covered a bunch of important data stuff, like how things work and fit together. The lessons were easy to follow and made sense.
Helped My Goals	This course matched what I wanted to do for work. It taught me the right skills for the job I was aiming for.
Good Teachers	The teachers knew their stuff and made it interesting. They talked about real things they’ve done, which made it cool.
Did Real Stuff	We did practical projects that felt like real work. It was useful to practice what we learned in the lessons.
Looks Good to Employers	People at jobs know about this certificate. They think it’s valuable and that I know what I’m doing.
Not Too Hard	It was challenging but not too hard. Even if you’re new, you won’t feel lost. It pushes you, but you can handle it.
Joined Discussions	We had quizzes and talked with others in a group. It was fun and helpful to chat about what we were learning.
Time was Doable	I spent about 8-10 hours a week. It fits with my other stuff, like work and stuff at home.
Got a Certificate	I did assignments, and then they gave me a certificate. It felt good to finish and get something for it.
Got Help When Needed	If I had questions, I could ask the teachers or others in a group. It wasn’t just me by myself.
Worth the Money	It cost something, but what I learned was worth it. The practical skills I got were more important.
Learned When I Could	I could learn when I had time. It wasn’t like a fixed schedule, so I could fit it in when I wanted.

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Now, let’s see the quality of content and projects.

Content and Projects of Coursera IBM Data Engineering Professional Certificate.

Coursera IBM Data Engineering Professional Certificate has 13 courses. Each course has modules, quizzes, weekly challenges, and projects. Now, let’s see how are the quality of the courses-

Course 1: Introduction to Data Engineering

• Duration: 12 hours
• Ratings: 4.7 (1,929 ratings)
• What You Will Learn: This course introduces the foundations of data engineering. You’ll delve into the core concepts of data management, understanding how data is structured and how it flows through various stages. Key topics include data pipelines, data quality, and the role of data engineering in modern organizations.

Course 2: Python for Data Science, AI & Development

• Duration: 23 hours
• Ratings: 4.6 (32,856 ratings)
• What You Will Learn: In this course, you’ll explore Python as a versatile tool for data science, AI, and software development. You’ll gain hands-on experience with data manipulation, data visualization, and implementing machine learning algorithms. You’ll also work with essential libraries like NumPy, pandas, and Matplotlib.

Course 3: Python Project for Data Engineering

• Duration: 6 hours
• Ratings: 4.6 (425 ratings)
• What You Will Learn: This course takes your Python skills to practical applications in data engineering. You’ll work on projects that involve data transformation, cleaning, and analysis. These hands-on exercises simulate real-world scenarios, enhancing your ability to work with data effectively.

Course 4: Introduction to Relational Databases (RDBMS)

• Duration: 18 hours
• Ratings: 4.7 (403 ratings)
• What You Will Learn: This course immerses you in the world of relational databases. You’ll grasp fundamental concepts such as data modeling, normalization, and database design. Practical skills include writing SQL queries to extract insights from structured data and understanding the role of relational databases in modern applications.

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Course 5: Databases and SQL for Data Science with Python

• Duration: 31 hours
• Ratings: 4.6 (18,100 ratings)
• What You Will Learn: Building on your understanding of databases, this course delves deeper into SQL and its applications. You’ll tackle complex queries, explore ways to optimize queries for performance and gain proficiency in using Python to interact with databases and analyze large datasets.

Course 6: Hands-on Introduction to Linux Commands and Shell Scripting

• Duration: 14 hours
• Ratings: 4.6 (825 ratings)
• What You Will Learn: This course equips you with essential Linux skills for effective data engineering. You’ll learn command-line navigation, file management, and shell scripting. These skills are vital for efficiently managing data, files, and processes in a command-line environment.

Course 7: Relational Database Administration (DBA)

• Duration: 20 hours
• Ratings: 4.5 (111 ratings)
• What You Will Learn: This course focuses on the role of a database administrator (DBA). You’ll delve into database security, performance tuning, backup and recovery strategies, and user management. These skills are essential for maintaining databases in optimal condition.

Course 8: ETL and Data Pipelines with Shell, Airflow, and Kafka

• Duration: 15 hours
• Ratings: 4.5 (227 ratings)
• What You Will Learn: This course introduces you to ETL (Extract, Transform, Load) processes and data pipelines. You’ll learn about tools like Apache Airflow and Apache Kafka, which play crucial roles in orchestrating data movement, transformation, and loading tasks.

Course 9: Getting Started with Data Warehousing and BI Analytics

• Duration: 17 hours
• Ratings: 4.3 (111 ratings)
• What You Will Learn: Data warehousing and business intelligence (BI) analytics are central to data engineering. You’ll explore concepts related to creating and maintaining data warehouses, as well as designing and generating BI reports to support decision-making processes.

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Course 10: Introduction to NoSQL Databases

• Duration: 17 hours
• Ratings: 4.6 (189 ratings)
• What You Will Learn: As traditional relational databases may not fit all data scenarios, this course introduces you to NoSQL databases. You’ll understand the various types of NoSQL databases, their strengths, and when to use them for different data models.

Course 11: Introduction to Big Data with Spark and Hadoop

• Duration: 12 hours
• Ratings: 4.3 (244 ratings)
• What You Will Learn: In the realm of big data, this course familiarizes you with technologies like Apache Spark and Hadoop. You’ll grasp the principles of distributed computing, data processing, and analyzing vast datasets. You’ll also explore frameworks for handling big data challenges.

Course 12: Machine Learning with Apache Spark

• Duration: 14 hours
• What You Will Learn: This course bridges data engineering with machine learning using Apache Spark. You’ll learn about data preprocessing, feature engineering, and building machine learning models. The focus is on practical implementation and understanding how to apply machine learning to real-world data.

Course 13: Data Engineering Capstone Project

• Duration: 11 hours
• Ratings: 4.6 (58 ratings)
• What You Will Learn: This final project is your chance to apply all the skills you’ve acquired. You’ll undertake a real-world data engineering project from start to finish, demonstrating your ability to manage data, design pipelines, and produce actionable insights.

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Summary of Courses

The Coursera IBM Data Engineering Professional Certificate comprises 13 courses that emphasize various aspects of data work. You’ll learn about data flow and how Python can assist with data tasks.

There’s a focus on databases, using commands in Linux, moving data around efficiently, and tackling challenges posed by big data. To wrap things up, you’ll undertake a project that lets you showcase your skills.

This program is all about making you an expert in handling data, creating databases, and using a range of tools for different data roles.

Coursera IBM Data Engineering Professional Certificate Cost and Duration

Coursera has three plans for this Coursera IBM Data Engineering Professional Certificate–

• For 1 Month, they are charging $49.
• For 3 Months, you have to pay $101.
• And for 6 Months, they are charging $144.

According to Coursera, if you spend 10 hours per week, you can complete the whole program in 5 months. But, It’s totally up to you. As the payment method is monthly, it’s better to complete it in less time.

If you want to complete this Coursera IBM Data Engineering Professional Certificate in one month, then you have to spend more than 20 hours per week.

And if you want to complete it in 3 months, then you have to give 20 hours per week.

But again, it’s up to you. Don’t rush to complete the program in under a month. If you are not able to give full-time to this Course. No worries! Learn according to your pace and time. Because what you will learn throughout the course is important not the completion speed.

So, this is all about the Coursera IBM Data Engineering Professional Certificate Cost and Duration. Now, let’s see the Pros and Cons of the Coursera IBM Data Engineering Professional Certificate–

What did I like about the Coursera IBM Data Engineering Professional Certificate?

1. You Learn a Bunch: This certificate is like a collection of 13 mini-lessons. They teach you all sorts of useful stuff about working with data.
2. Big Name Learning: It was created with help from IBM, a big company that knows tons about tech and data.
3. Try It Out Yourself: The best way to get good at something is by practicing. This certificate lets you do fun exercises and projects to practice what you learn.
4. Become Good at Many Things: You’ll become skilled in things like using a computer language called Python, managing databases, moving data around, and even handling really big piles of data.
5. Get a Cool Certificate: When you finish everything, you get a special certificate. It’s like a shiny award that says you’re super good at data stuff. It can help you show off to people like bosses when you’re looking for a job.
6. Learn Whenever You Want: You can learn when you have free time because the lessons are online. You choose when to study.
7. Fun Lessons: The lessons are like watching videos, playing quizzes, and doing fun things. They keep you interested and make learning feel like a game.
8. Teachers Who Get It: The people teaching you are really good at data stuff. They talk like regular people, not boring book words.
9. Show Off Your Skills: At the end, there’s a project. You get to show what you learned by doing a real project. It’s like proving you’re awesome at data stuff.
10. Make New Friends: You can talk to other people and learn the same things in special online groups. You can ask questions and share cool stuff you find.
11. Get Ready for Cool Jobs: After you finish, you can look for jobs that need data skills. This certificate helps you show you’re a data pro.
12. Learn Forever: Once you’re in, you can come back anytime you want to learn more or remember what you learned.

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What I didn’t like about Coursera IBM Data Engineering Professional Certificate.?

1. Time and Effort: Doing 13 courses takes a lot of time and work. It might be hard if you’re busy with other stuff.
2. Could be Tough for Newbies: Some courses cover advanced stuff that might confuse you if you’re new to data work.
3. Need to Know Stuff First: Some courses expect you to know things already, which could make it harder if you don’t.
4. Costs Money: Getting the certificate might cost money, and that might be tough if you don’t have much.
5. Some Courses are Better: Since different people make the courses, some might be better quality than others.
6. Job No Guarantee: Even if you finish, it doesn’t mean you’ll get a job right away. You might have to look hard for work.
7. You Lead Yourself: It’s up to you to learn without a strict schedule or teacher in front of you.

My Personal Suggestion

Once you finish the Coursera IBM Data Engineering Professional Certificate, think about what you learned and update your resume and LinkedIn. Show off the projects you did. Join the data people community, think about what you like most, and start looking for jobs or internships. Tell employers about your skills and learn more to stay on top of things.

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And here is the Coursera IBM Data Engineering Professional Certificate Review end.

Conclusion

I hope my Coursera IBM Data Engineering Professional Certificate Review will help you to make your final decision. If you have any questions, feel free to ask me in the comment section. I am here to help you. If you found this “Coursera IBM Data Engineering Professional Certificate Review.” helpful, share it with others to help them too.

Happy Learning!

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