Preparing for Data Science roles can feel overwhelming — scattered resources, unclear direction, and too much noise.
That’s why I’ve built a curated, structured resource library to help you stay focused and interview-ready.
This collection brings together everything I’ve used and refined while mentoring 1000+ professionals into successful data careers.
📂 DSA – Most commonly asked logic-based and coding problems
📂 SQL – Foundational to advanced topics: joins, subqueries, window functions
📂 Python Basics & Coding – Practical, interview-relevant code examples
📂 EDA – Business-focused exploratory analysis frameworks
📂 ML – Model intuition, evaluation, and real-world applications
📂 Deep Learning, Generative AI, Agentic AI
📂 Optimization – Scenario-based problems with real impact
📂 Most-Asked Interview Questions – Directly from top company interviews
📚 Open-Source Resources (Included Free) – Handpicked, high-quality open resources added inside the kit at no extra cost.
• Data Analyst, Data Scientist, and ML Engineer aspirants
• Professionals preparing for interviews at product firms, startups, or MNCs
• Anyone seeking structured, high-impact preparation
⚡ These are not generic notes.
They’re battle-tested resources, refined through real interview experiences, mock sessions, and success stories.
🔄 And yes — I’ll be updating this library regularly with new questions, advanced topics, and insights to keep you ahead.