How can I grow from a data analyst to a data scientist?

Data Science, AI and ML
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#1
Data Analyst and Data Scientist has a lot of roles and responsibilities in common – depending upon the industry or company that the individual is engaged in. However, in general, students need to develop their skillsets and acumen in the field of statistics to make a transition from data analyst to data scientist. Students can scale up in statistics starting from basic probability & algebraic concepts; and then progressing towards more complicated stuffs.
Another important concept which data analyst needs to upskill to become a data scientist is coding, specifically in Python as this is a mandate for developing data science models and algorithms.
#2

Data scientist and data analyst are the same thing called differently in different companies.

What do you use SQL and Excel for? Just making reports? Then you are not really a scientist or an analyst You are, what we call in KSF, a reporting analyst that just takes an order and makes a report with no ad-hoc analysis done to the report.

A data scientist or analyst goes into the details. He/she dives into each column of his data and finds everything that is to find in there. Percentages, shares, distributions, correlations between variables, outliers in 1, 2 or more dimensions, transform your data and look at it again. Really, the tools that you are using don’t matter. What matters is what you use them for.