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Jan Schwarzlose Courses
Writing production-ready ETL pipelines in Python / Pandas
4.3 (894 Reviews)
Provider: Udemy
Time: 7.1h- 2022
$59.99
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Most Recent Review
I think the course was a very ambitious venture into what is a complicated process of creating a production-ready ETL job. The earlier parts of the course were great for understanding the process of moving from a quick and dirty solution to a production ready script, utilizing different programming practices. However, the testing part of the course became very difficult to follow, and at some points, impossible to follow. It felt like the instructional parts of these courses were too quick (which may be due to the complexity of the concepts) but it felt a bit too fast and unfocused.
- Review by Nile Williams on Writing production-ready ETL pipelines in Python / Pandas
Instructor Bio
Es gibt so viele coole Tools da draußen - vor allem im Bereich Small/Large/Big Data. Ein Leben reicht garnicht aus, alle Tools zu kennen und gut darin zu sein. Aber bereits mit einem übersichtlichen und guten Toolset kann man tolle Projekte mit echtem Mehrwert umsetzen.
Ich habe 2012 die Universität als Diplomingenieur für Mechatronik abgeschlossen, wobei Programmierung vor allem im Embedded Umfeld eine wichtige Rolle spielte. Im Laufe meiner ersten Berufsjahre als Ingenieur entdeckte ich mehr und mehr meine Leidenschaft für Python vor allem mit Small/Large/Big Data.
Nach einigen Hobby-Projekten wagte ich 2016 schließlich den Schritt auch beruflich in diesem Umfeld zu arbeiten. Nun arbeite ich seit mehreren Jahren erfolgreich als Data-Engineer und hatte die Möglichkeit in tollen Projekten mitzuwirken.
Dieses Wissen möchte ich gern durch Kurse im Bereich Data-Engineering und Data-Science mit einem hohen Fokus auf die Praxis weitergeben.
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English Version
There are so many cool tools out there - especially in the small / large / big data area. One life is not enough to know all tools and be proficient with them. But even with a quite small and good toolset, you can implement great projects with real value.
In 2012 I graduated as engineer for mechatronics. Programming especially in the embedded area was an important part of my education. During my first years as an engineer, I discovered more and more my passion for Python, especially with small / large / big data.
After a few hobby projects, I took the step to work professionally in this area in 2016. I've been working now for years as a data engineer being involved in great projects.
I like to pass this knowledge on through courses in data engineering and data science with a high focus on practice.
