I get this question a lot, “Is it necessary to learn to code for data science work?”
Here is my take.
The need to learn coding is currently driven by the tools used by data scientists. If you happen to be in an organization that uses point-and-click tools, for example, Excel, Tableau, then you do not need coding…at the moment. The reason is open-source tools are currently eating up the market share of these point-and-click tools. I have seen the adoption changed tremendously, especially in the last few years.
What is the proficiency level needed? A lot of companies are starting to move towards being data literate. Which means (almost) all the staff needs to handle data going forward. Again, depending on the tools use and the job requirements, the proficiency level will differ. But learning to code, is getting easier as compared to my undergrad days, more than a decade ago. Check out my article here.
That is why I strongly encourage you, the subscriber, to learn to code. It will make your Data Science career more robust, and not be limited to working for organizations that use point-and-click software (remember their shrinking market share).
In conclusion, you are strongly encouraged to start learning to code, even if you foresee you will not be using it in the near future because changes to the working environment can happen quickly and coding is a skill that will go a long way.
While you are learning to code, check out this post on the best practices I come across.
All the best in your learning! If you find this newsletter to be useful, consider sharing it and like it by clicking the heart shape on top. Let us stay in touch on LinkedIn or Twitter too. :)
Posts you might find useful:
Data Scientist Needs Business Acumen
Starting the Artificial Intelligence Learning Journey
Building the Data Science Thought Process
Posts since the last newsletter:
Lex Fridman Interview - Greg Brockman
Coding Best Practices for Beginners
Books I am reading now:
Upheaval: Turning Points for Nations in Crisis
Rethink: The Surprising History of New Ideas
Human Compatible: Artificial Intelligence and the Problem of Control