I found Op's link didn't work well I think this is the course he was trying to link to: https://www.udemy.com/course/data-engineering-essentials-sql-python-and-spark/

>Sir you are in a class of your own. What do you feel about this course?

First of all it really depends on what kind of role you want to do in data Engineering. As I mentioned before there's a wide spectrum of roles. However Assuming we're looking for the most common role of Data Engineer managing enterprise Data pipelines with some flavours of Spark and Python scripting then here's my thoughts on your course.

+ It's a specific Intro into Googles Cloud offering.

- It's a specific Intro to Googles Cloud offering

To elaborate a bit Things like Cloud Spanner and Big table are for very specific use cases and Beam is pretty cool but again a little bit Niche these days.

My gut on this course is you'd probably learning a lot of specific tools for the "Google Cloud" way of doing things and the course is very light on the 99% of work being done once the infrastructure is set up. And even then Infrastructure as code tools like terraform make a lot of the content on "which button to click in the UI" etc redundant.

If we define a "good" course as giving you the tools and the basic knowledge to set yourself up and work on "data engineering" tasks. Then a search found me this course which I think is very suitable for someone getting into DE Because

- Decent primer to Python, the most common language you'll find in DE (undeniable fact even If I work with Scala mainly). If you have some Perl you should be able to breeze through getting up to a scripting level with Python.

- Covers some basic cloud stuff (aka set up a server) mainly for the purpose of setting up a database.

- Covers Docker and setting up a database in Docker. I approve of this because manually configuring a database on a remote cloud server and THEN starting to work on SQL and modelling is a bit like learning to Drive a car by first assembling a car with 0 prior knowledge, no it isn't hard if you have previous knowledge of accessing remote servers, working in a Unix system, dealing with network ports etc, but there's a lot of moving pieces to know upfront.

- Docker is also a technology pretty much everyone is using or intends to use so well worth learning), dockerising applications you'll need to know to even start to work with Google App Engine or Elastic Container Services etc.

- I'm assuming you have some decent knowledge of networking already but if not then it goes over Hosts and Ports and stuff you'll need to know to stick together all these services into a coherent system which I feel a lot of courses glaze over a bit.

- Covers SQL (ok you're familiar with this but this goes into a bit of depth on how to build a data warehouse properly)

- Covers Spark which is a little more specialised for Big Data use cases but also very common. Most importantly how to use Spark in Python rather than introducing Scala which is a whole new way of thinking to Learn.

If you have these skills then knowing how to configure a managed DB instances in GCP and using it is just a higher level of abstraction on top of this.

Work through this alongside acloud skills course and I think that's a pretty ok grounding in both Basic Software/Data Analysis skills and How to use them in a cloud.

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>Also please give me the name of the O'Reilly Book.

What I meant by this is if there is a specific technology you want to deep dive (e.g Spark) then O'Reilly normally have a world class book on it written by some sort of Deep expert/Software Author on the topic so that'll normally be my start point. If I'm going to chuck out a specific book then there is a book everyone gets recommended on here called "Designing Data Intensive Applications" which is a very good overview of most of the Topics of Data Engineering while also going a little bit Deeper into important slightly deeper technical knowledge like how Indexes work that you should pick up eventually. I'd recommend everyone reads that cover to cover as it covers a lot of stuff and it's also very well written even for someone not hugely technical.

Great, first of all, best of luck with your endeavor to become a Techie especially in the area of DE.

If you are aspiring to be a DE, I will suggest you learn with realistic examples instead of getting into complex algorithms. You can also see if our playlist is helpful. It will guide you through to setup jupyter based lab with data sets to practice. You can also sign up for our Data Engineering Essentials hands-on - Python, SQL and Spark course on Udemy. Typically it is available for around $10. You will also get the required support on the content from me as well as my team.

Data Engineering Essentials - SQL, Python and Spark

https://www.udemy.com/course/data-engineering-essentials-sql-python-and-spark/