Advice on where to continue in the field of data engineering and machine learning

Dataquest is a great place to start. It will help you bridge the gap from just learning to actually coding as a data analyst, data engineer, or data scientist. Unlike most online courses, there are no videos, and they provide an interactive coding and learning environment that makes it very easy to learn the practical techniques you'll actually need to work on real-world data and problems.

The best part about Dataquest is their guided projects that are part of every topic you learn. If you want to eventually get a job as a data analyst, scientist, or engineer, you are going to need a portfolio of projects to show what you know, and Dataquest helps guide you through the entire process.

fast.ai is another great place to learn about machine learning, and deep learning in particular, all for free. They teach using a top-down approach that will get you working on your own projects and data in no time.

First of all, Congrats that you have started your journey of becoming a Data engineer/analyst. According to me there is no clear path on how to become a Data analyst.

Applied data science with Python course is great but i would urge you to start working on problem statement of any domain (NLP,CV) and take part in competition where you will learn how to visualise data and work with large amount of dataset which are key requirement on becoming Data engineer/analyst. In this process you will anyway get to know what you need to learn and apply to solve the problem statement.

Remember this will be a long journey so keep hustling!

There a three dimensions of knowledge you need to be a generally competent data scientist:

1. Statistical / Mathematical knowledge

2. Programming / CS skills

3. Domain knowledge

I think studying and courses help in 1) and to a degree in 2) but not at all in 3. If you feel confident enough in 1/2 that you can solve some real life cases it would be best to start doing projects (Kaggle, your own projects, etc.).

Otherwise you should focus on applied courses that combine 1 & 2 in a target oriented way. I am very partial to the Kaggle micro-courses because they are small, practical and fast but you need some basis to do these.