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If I had 30 days to learn SQL and Python for data analysis, this is the exact plan I would follow. And no, I would not spend all 30 days watching tutorials. During the first week, I would focus only on SQL basics. For example, select, where, group by and aggregate functions. You can use SQL Zoo to learn each concept, but after every lesson, write the query again without looking at the answer. During week two, move to joins, CTEs and window functions. You have to complete at least one SQL problem every day. Try it yourself first, then use AI to review your code and explain what you got wrong. Week number three is where you'll get started with Python for data analysis. You do not need to learn every part of Python. I think this is the mistake a lot of people make focus on pandas and learn how to load data, clean it, filter it, group it, merge it and basic visualization. Kaggle has Python and Panda courses you can use for this. Then I would spend final week building one complete project. You can pick a sales or customer attention data set you seek will to answer the business question. I don't to clean it and analyze the data or Tableau and power BI to present the results. Then upload the project to GitHub with a read me file. This is key. Read me file that explains the problem, your process and what you discovered. After 30 days, you will not know everything, of course, but you will have something more valuable than another certificate. You will have a complete, complete, complete SQL and Python to solve a real data problem. And that is the key. And of course, you already knew this because you follow me. Let me know if I should turn this into a complete day by day checklist so you can follow along.

If I had 30 days to learn SQL and Python for data analysis, this is the exact plan I would follow. And no, I would not spend all 30 days watching tutorials. Du…