Course content is good but labs are riddled with bugs and in dire need of quality control. I encountered many time-consuming, frustrating technical issues that made completing this course a slog. Final assignment introduces some difficult linux manipulations that were not covered in the coures and are not really that relevant to the subject matter. Some questions on the final are unclear and could be better written. Would recommend the instructors or whomever created this course to eat their own cooking and go through this course and fix the various issues.

Buggy practice. Not possible to complete without fixing airflow start script yourself. Nobody monitor or fixing issues here

The course is really basic, it only introduces the keywords and very high level concepts of ETL. Barely discusses any technical challenges or constraints. Some of the questions in the quizzes are absurd.

I cannot proceed with the "SUBMIT a DAG" lab as I am constantly being shown the error - "cp: cannot create regular file '/home/project/airflow/dags/my_first_dag.py': Permission denied" when I run the command - "cp my_first_dag.py $AIRFLOW_HOME/dags".

How are you expecting me to complee this lab when I am getting a permission denied error. Please fix this asap.

Thanks to IBM and Coursera for the great "ETL and Data Pipelines with Shell, Airflow and Kafka" course, that I passed with Grade Achieved: 100%. It's the third course, that I've passed, as a part of "IBM Data Engineering Specialization". I was so carried away by the course that I literally sat up until 2 am almost every day. In this course I could apply my knowledge of Python, Pandas, SQL, Bash commands to build ETL Batch and Stream pipelines.

The final project to connect Airflow as a pipeline management tool to Kafka server is a very useful hands-on project. More details or explanations on the syntax of Python calling Kafka producer and consumer, which are in the files of toll_traffic_generator.py and streaming_data_reader.py, would be more valuable rather than just providing these two files to run on its own.

It's one of the most challenging courses I've been enrolled!

REALLY A GOOD COURSE BUT:

- Labs are not debugged (inaccuracies)

- I understand that Kafka a wide technology and maybe it will take more than a week to cover in a appropiate way, but the labs were only about copy and paste commands.

I can't understand some of the questions in quizzes. Moreover, the peer-to-peer grading system should be converted to automatic grading.

Perfect environment to make experiments! Very easy and powerful in use.

It's great introduction for airflow and kafka but still an introduction it is shallow doesn't offer much but at the end you will understand what you need to continue further in both technologies.

Love the labs, but do not like the robotic lectures.

final quiz sucks!

why are you so sick to make up this quiz ?

this quiz is pretty much more like GMAT reading test instead of IT assessment !

Interesting course with enough labs.

i really liked the labs

A decent overview of Airflow and Kafka. Worth it for the time invested. The labs were good, however the execution of the final assignment was poor -- you have to submit two dozen screen captures for a peer reviewed assignment. Taking screen caps of code is silly, why not just submit the code? Plus you are taking the caps before you even know if your code works. And you are relying on strangers to read and understand your code before you can get credit for the course. Fortunately, some kind soul found mine quickly and gave me 100%. My code did work -- I tested it thoroughly -- but you can't really tell from screen caps.

A good introductory course to airflow and kafka. Could have been broken up into at least two courses focusing on each of these platform, and going more in depth in each one. Also, the final assignment is a pain to complete especially due to some errors in instructions. But overall, It is a decent course.

A good overview and introduction to using Airflow and Kafka. The quizzes are lazily written and ask specific rather than generalisable knowledge questions. The final assignment for Airflow was great - lots of coding and debugging. Kafka not so much - just paste commands and watch it run.

It would be much better with real instructors and with no peer review that is not objecitve and no proper ansers clue

The course material was basic so make sure do to a lot of your own additional learning outside of the coureswork. The discussion staff are not helpful/don't understand or even read your questions before replying. The labs don't always work and the instructions don't always line up with current software upgrades. Just be prepared to do a lot of troubleshooting with not much help. I wish the course would tell you what to do when certain errors occur/are more thorough with their instructions.

Ok, Very good course, but during the exam the focus was a very difficult part made of commands of Linux Shell, expecially dealing with files that are not CSV. That was not the main focus of the course, actually.....

The labs in the module lacked proper planning. Connecting to servers consumed excessive time, and errors meant reconnecting, often without success. The instructions provided by instructors were vague, suggesting solutions like 'try using other networks,' which prolonged the process. Sadly, this meant spending a month solely on server connections instead of delving into the ETL process. There was a significant amount of time wasted. Moreover, the lectures could benefit from a more contemporary approach beyond a mere slideshow. Additionally, the lecturer's voice was somewhat grating; it felt almost artificial, prompting the question of whether it was actually a human reading the slides. It might be worth considering this aspect for future presentations.

I feel though the final project suffered from issues with permissions, and there was a lack of a standard setup. Where should DAG scripts go? Why should they be in a folder with admin only permissions? Submitting screenshots is tedious and (frankly) shows a lack of willingness on the part of the course designers to use tools like nbgrader/Jupyter notebooks or other automated grading solutions.

Warning, if you can write a "Hello World" program in any language, you probably want to skip this course/certification.

This is a well-crafted course about ETL and building/streaming Data Pipelines. The hands-on labs experience including practicing shell scripting prepared well for the final assignment task. Writing the real-world-scenario DAG tasks to create the ETL Data Pipelines using Apache Airflow was challenging. Successfully submitting the DAG and monitoring it in the UI DAGs list was at the same time satisfactory.

Great course! I found the challenge intensity for the final peer-graded assignment to be at a perfect level for this course. It brought together many skills from this course and several previous courses in the IBM Data Engineering Professional Certificate curriculum.