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Learner Reviews & Feedback for Introduction to Data Engineering by IBM

4.7
stars
2,779 ratings

About the Course

Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem. You will begin this course by understanding what is data engineering as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in this exciting field. Next you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will become familiar with the components of a data platform and gain an understanding of several different types of data repositories such as Relational (RDBMS) and NoSQL databases, Data Warehouses, Data Marts, Data Lakes and Data Lakehouses. You’ll then learn about Big Data processing tools like Apache Hadoop and Spark. You will also become familiar with ETL, ELT, Data Pipelines and Data Integration. This course provides you with an understanding of a typical Data Engineering lifecycle which includes architecting data platforms, designing data stores, and gathering, importing, wrangling, querying, and analyzing data. You will also learn about security, governance, and compliance. You will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. You will hear from several experienced Data Engineers, sharing their insights and advice. By the end of this course, you will also have completed several hands-on labs and worked with a relational database, loaded data into the database, and performed some basic querying operations....

Top reviews

MF

Mar 25, 2022

This course is optimal for the foundations and understanding of Data Engineering. Please take it and absorb all the knowledge and be amazed about your future with the Data Engineer certification.

OU

Oct 12, 2021

I am currently studying Chemical Engineering. However, after going for industry training as a data analyst, I decided to venture more in this direction and I really learn a lot from this course.

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551 - 575 of 610 Reviews for Introduction to Data Engineering

By Pallavi P

•

Jan 13, 2022

Very Good Contents and nicely explain

By Ahmed B

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Oct 27, 2021

best for a all round starting course

By Andrès M

•

Sep 19, 2024

Tal vez más ejercicios prácticos

By Robert K

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Oct 23, 2022

to fast for non english speaker

By S V

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Feb 13, 2022

More theoretic, less practice

By Muhammad S

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May 29, 2023

Interesting and informative

By Ziad A

•

Oct 24, 2022

Great Introduction Course

By Kouakou B K

•

May 8, 2023

Educational for bigenners

By Manuel G C

•

Jan 13, 2022

Good introduction course

By Leon M

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Jun 22, 2024

i recommend this course

By Akinbuluma T

•

Aug 17, 2023

Nice and informative

By kamsii o

•

Sep 23, 2023

Very Comprehensive

By Hopeton M

•

Oct 25, 2021

loved the course

By Sheraz M

•

Aug 13, 2021

Informative

By Paitoon p

•

Apr 9, 2023

Good course

By Garrick B N

•

Jun 2, 2023

very good

By Pedro Q

•

Apr 28, 2022

Exelente

By Nadia A H P

•

Jul 11, 2021

Amazing

By khalil d

•

Oct 22, 2024

good

By Mustafa S d A

•

Aug 22, 2024

bien

By kartikey m

•

Jul 3, 2024

best

By Shubham G

•

Nov 25, 2023

Nice

By 21O18 K F

•

Jul 13, 2023

Good

By Tom W

•

Sep 26, 2024

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.

By Valerio M S

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Apr 5, 2023

Very basic, too much interviewing people and few content.

The IBM Cloud account setup fails very often, issues with keys and required to send emails.

Few questions are misleding if not wrong:

- the one asking which one is an example of semi-structured data where both emails and Tweets are actually semi-structured data.

- Other example the one asking to count unique values in a SQL statement where COUNT and DISTINCT are two options while the correct answer should be COUNT DISTINCT