I've been a data guy for first half of my career in service company and was mainly using sql and gui etl tools. However in the second half I started to move towards R and Python for data engineering and science stuff. Although exploratory coding is fine with me I find real time coding during interviews very grinding. Any suggestions to overcome that. I'm a data scientist at age 38.
Like everything, start easy and break it down. Meaning, start by writing code for all sort types, then focus on all easy array and string problems. This help you with simple problems involving basic loops and branching. You’d realize importance of loop invariants, pre and post conditions. Then move into basic recursion and trees. Follow any book like ctci or epi for progression. Once you get comfortable with these basics, it will help to do Michael interviews on gainlo. It is a process with no shortcut. In the end the reward is big. Also interview kickstart is also good idea but it cost you.
Blasphemy!
If you've been doing it for some time, I suggest going to hard ones now. Time box to 40 minutes in coming up with a solution. If you can't make progress beyond that time, look at discussion for solution. Understand the solution and add a tag to revisit it in one month. After one month try to solve it again with code accepted by oj. Spend no more than 1.5 hours total on each question on your first attempt.
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practice makes perfect! give it a time - leetcode every day/other day and in 2 months it’ll be a dramatic difference in terms of nerve. Do all easy ones first