I learned something from this course, and was prompted to read around the topic and view some videos which was valuable to me. It give me an idea of the field of "data engineering" and it gave me pause to think about the role itself. I didn't really like the material however. Lots of the questions had a feel of "say the right thing" (business, business, business) which felt like being at schoool. It's like, yes stakeholders and business value are important but you don't have to remind me all the time. I didn't really like the "professional" part of the role, though that is what it ends to do. I guess I don't view myself as a "cog" with skills - perhaps a foolish vision - since life is simpler if you view the world like this but that is off topic. Some of the distinctions and terminology seemed entirely academic and not necessary relating to reality. The concept of "data pipeline" seems a bit meaningless - it mostly seems to mean "doing data engineering". DB2 seemed a bit oversold, it felt like advertising put into the course. It was good to get a list of tools for different purposes, and it was good to be introduced to what people think is trendy.

This is listed as a "Beginner" course, but I don't think so. They use terminology, and then don't explain what that terminology means in the moment...if at all. (e.g. API, Relational Database, NonRelational Database, Data Warehouse, Data Mart, Data Lake. Their explanation of Delimeter wasn't good). I have at least a dozen things I had to Google, and I marked them as such.

Things that don't need repeating or further explanation get exactly that...it's very odd.

Also, One of the Practice Quizzes contradicts the Graded Quiz re: whether XML format is used by APIs (I have a screenshot.)

Advice to the Creators:

It's October 2021. Nobody has the bandwidth, spoons, or patience anymore. Hell, we only have the Bones a few days a week, at most. (Pending confirmation from Noodle, of course). TL;DR as much as possible, and CLEARLY EXPLAIN the rest IN THE MOMENT, TO PEOPLE WHO ARE BEGINNERS TO TECH.

Thank you.

I do think there's more highly engaging courses out there. It's also too theoretical and not so practical and it needs updating. It generally is okay to get a better view of the data eng landscape.

The course could be very good. However, the female AI voice chosen for the voice over in many videos is so fake and irritating that it is difficult to concentrate on the material being covered.

The peer review is a total joke and will hinder you from successfully completing this course due to some random dude in some random country spitefully grading people low.

I didnt learn ANY practical skills.

ccourse Feedback: Data Engineering Course Content Quality: The course material was comprehensive and well-organized, covering all the essential topics in data engineering. The inclusion of both theoretical concepts and practical applications provided a balanced learning experience. However, I felt that some sections could benefit from more in-depth explanations, particularly on advanced topics like Big Data and Spark. Instructor Effectiveness: The instructor was clear and engaging, making complex topics easier to understand. Their use of real-world examples helped to contextualize the material. However, there were moments when the pace felt a bit rushed, and additional examples or explanations would have been helpful. Practical Application: The hands-on projects and real-world examples were a highlight of the course. They allowed me to apply what I learned in a practical setting, which greatly enhanced my understanding. The projects were well-designed and relevant to current industry practices. Course Structure: The course was well-paced, with each module building logically on the previous one. The progression from basic to advanced topics was smooth, and the quizzes at the end of each module were useful for reinforcing the material. Resources and Support: The additional resources, such as readings and videos, were very helpful. The forums provided a good platform for discussion and support, although response times could be improved. Overall, the support was adequate, but there is room for enhancement in terms of timely assistance. Overall Experience: Overall, I am very satisfied with the course. It provided a solid foundation in data engineering and equipped me with practical skills that I can apply in my career. I would definitely recommend this course to others interested in the field.

The Introduction to Data Engineering course exceeded my expectations! It covers a wide range of topics in a well-structured manner, from data ingestion to processing. The instructor's explanations are clear and concise, making complex concepts easy to understand.

What sets this course apart is the emphasis on practical exercises and real-world examples. They provide valuable hands-on experience in data engineering techniques. The course materials are comprehensive and organized, serving as useful references.

If you're interested in data engineering, this course is a must. It provides a solid foundation and equips learners with the necessary skills for building efficient data pipelines. Highly recommended!

Kudos to the instructor and course creators for an exceptional learning experience!

I took this course as part of the "IBM Data Engineering Professional Certificate". As mentioned in the title, it is an introductory course and hence was quite theoretical and conceptual.

Even though it is theory, concepts are explained clearly and with examples. The "perspectives" videos from industry professionals make each topic come alive as it feels like you were the one to directly ask the people questions and are listening to their response. It also makes the section less dry.

Overall, I feel confident in my understanding of Data Engineering now. The only nitpick is that there is quite a bit of information to digest and it's better if you take running notes (helps revise for assignments as well)

I would like to say big thank to coursera to give me this opportunity to learn IBM Data Engineering and I understand now the difference between data science, data analysts , big data and database administrator , and I understand how to open IBM cloud account and how to use a SQL and I get what exactly a data engineer can do in the job life . I finish my introduction and I’m excited to move to the next level to know more about Python, database,SQL ETL , DBA ,NoSQl, big data , Spark and Hadoop , Machine learning. And I recommend everyone to start study on coursera is the best website to learn 💕💪🫡

Je suis formateur spécialiste polyvalent des TIC "MOS Expert, Instructeur Cisco CCNA, RHCE, ...". Depuis peu de temps, le monde de Data m'a impressionné et m'a attiré l'attention. Conscient que le future appartient à ceux qui maitrisent les données, j'ai abordé ce sujet de proche, et au bon milieu du chemin, je découvre une "forteresse" de cours IBM dispensé par Coursera, des cours bien expliqués, bien illustrés et bien enchainés. Les Labs sont aussi d'une valeur ajoutée. Un avantage de plus est la possibilité de suivre les cours à mon rythme.

Great Learning & gain Exceptional Knowledge The Introduction to Data Engineering, Me to Understand All Areas of Data Engineering Concepts and a solid understanding of the fundamentals of data engineering, big data engineering, and database administration. , This Course Absolute to Right Who wants to be a Data Engineer, Big Data Engineer, DBA & More, This Course to Concept Building Large Scale Data Design & Data Platforms, Thanks a Million & Million to Coursera & IBM to Publish this course

I took this course without having any prior knowledge in the data engineering or even computer science field, and it has taught me so much about the basics of data engineering. Sometimes during the course lessons however I found myself losing focus as some of the topics are repeated throughout the course lessons. All in all I would recommend this course to anyone that would like to enter the career of data engineering or would like to brush up on the basics of data engineering.

This course is very fundamental in building my understanding and knowledge about data engineering. It has made me understand the many professions in the field of data engineering and how it cannot be done by one person alone. This has also gave insights on what skills I need to upgrade in as the Data Manager in our organization that has no background in data engineering, computer engineering, computer science or any related field.

Well Defined Structure in the course defining the essential knowledge one needs to have to start off a career in Data Engineering. Gives information about the tasks that a Data Engineering has to perform as a routine and different specialization that may suite to one's interest as well. Recommended to start with this course to know whta you are getting into if you are planning to become a successful Data Engineer.

Course is awesome to understand who are already working or who wish to jumpstart their career path in Data Engineering domain to make their decision about 1) which data repository should they used, 2) what kind of data store should be , 3) how to select the their production databased based on their need. Systematic, clean, neat and step by step approach make us easy to learn and remember key artifacts too.

Really thorough overview. I appreciate the encouragement, but also reminders, of the importance of different skills required for this job, hard and soft. Loved listening to the viewpoints, especially from Xiao Yang, who found success despite the lack of background in this field. I assume many others who are on MOOCs are in a similar boat. Thank you!

Great learning this course from Coursera and its team. For every chapter Quiz's and individual assignments helped me to assess my learning knowledge continuously and consistently. Thanks to Coursera for helping me to achieve this introduction certification. Looking ahead for other courses to achieve my IBM Data Engineer Professional Certification.

The course content is a very well-structured, especially for me as a beginner. The viewpoints from the people who working as data engineer was five stars. The text transcript are very helpful too. The instruction for lab session easy to understand, except that some of the image a little blurry (but readable still), so it was okay.

A very detailed introduction and a great general overview of the Data Engineering profession and body of knowledge. Would definitely recommend for anyone looking at starting a career into the data engineering field. The course covers all the content that are absolutely necessary to know and understand at a foundational level.

Excellent course. All the presented information is presented in an very clear way, anyone with the intention of learning these topics shouldn't have any problems understanding the concepts. I recommend taking notes in from every lessons, because the material is dense and quizes forces you to really understand the concepts.

This course has a quick pace and is very engaging! So far, this is one of the best courses that I have taken as someone who has a degree. The pace feels similar to that of a college-level course rather than a slow beginner course. This has allowed me to actually stick with the program because I have stayed interested!

This course is awesome. It introduces the concept of data engineering so well while comparing it to other data-related fields such as data analysis, and data science.

I really liked the expert viewpoints on different subject matters - they helped give real-world perspectives too.

A big thank you to IBM for this course.

In my idea this course is very good starting point to data engineering field. The content is great because instructors try to build and represent big picture of domain knowledge, tools and technologies involved in this field. My special thanks to Coursera for bringing high-quality learning materials to eager people.