I built a diagnostic test because "proficient in SQL" means nothing

I'm 6 months into a self-directed data science program. Every day I study SQL, Python, stats, ML, and BI. But there was one question I couldn't answer:

Am I actually ready?

Job descriptions say "proficient in SQL" — but what does that mean? Can I write a window function from memory? Do I really understand p-values, or can I just explain them?

I needed a way to test myself that wasn't:

1. Another tutorial (passive learning)

2. A Leetcode-hard problem (demotivating)

3. Just guessing (useless)

So I built the Data Skills Assessment Pack — 5 mini-tests covering the core skills every data analyst job asks for:

• SQL (15 questions)

• Python/Pandas (12 questions)

• Statistics (12 questions)

• Machine Learning (12 questions)

• BI & Visualization (10 questions)

Each test mixes MCQ, short answer, and practical prompts. Score yourself, see your level (Beginner / Intermediate / Advanced), and get a roadmap for what to study next.

Pricing: $12
Link: https://deepanshu647.gumroad.com/l/thbgix

Would love feedback — what would you add to a data skills assessment? What's missing?