If I have finished a career track (data scientist) from any MOOC platform , what should be my next step?

Set some real-world expectations. You are looking at 5–8 years before you working at any real company as a machine learning engineer.

Here, I’ll help set some expectations.

Most applied data science is machine learning so if you want to work in the real-world I’d learn machine learning.
—There are ZERO entry level jobs in machine learning, even the ones that have entry level require heavy Python, SQL and experience.

The job may say entry level but they want data and Python experience.
Most MOOCs doesn’t teach applied machine learning so I’d suggest you find a platform that does.
Without heavy SQL knowledge, you’ll be unemployed so I’d suggest you start learning SQL.

Since there are no entry level jobs in machine learning, you’ll need to take a job at the lower end… a data analyst or business analyst, something working with data.
Finished often doesn’t mean you studied the material. The technical interview for machine learning is brutal,

I hope you studied the information and wrote down all the code and can use it.
I’d recommend an SQL certification. It won’t guarantee a job but will get you an interview. I’d pick a Microsoft one, their database called SQL Server is the most prevalent in the applied space.

How are your data cleansing skills? Around 80% of the work in machine learning is data cleansing. If you don’t have these skills companies don’t want you.
How about applied statistics? Without heavy stats skills you’ll be unemployed.

If I were to ask you, what model would you choose for classification? Most real-world problems are classification problems so you should know what model is the king when building classification and regression problems.

Now, this shouldn’t discourage you. If you want it, you’ll make it happen. However, the barrier to entry in machine learning is brutal so set some goals and realistic expectations.