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Before you begin your data science journey, I want to emphasize that this comprehensive roadmap is not meant to overwhelm you. Instead, it’s designed to keep you informed and guide you step by step. You can tackle it one piece at a time. Here are a few things I’ve learned along the way
Progress Takes Time: Learning can be a mix of easy and tough stuff. Just keep at it, even if you don’t see results right away.
Five Key Qualities: To succeed in this field, you need patience, consistency, belief in yourself, good prioritization, and time management.
Take Breaks Wisely: It’s important to recharge, but make sure breaks don’t turn into excuses to lose sight of your goals.
You Don’t Need to Learn Everything: Tools change quickly. Instead of trying to know it all, focus on analyzing data, getting insights, and revisiting what you’ve learned.
Step Out of Your Comfort Zone: If things get tough, remember that you’re growing, not failing.
Follow Your Passion: Don’t just go into data science for the high pay—find what you love to keep yourself motivated and avoid making excuses.
These are unique and engaging characters that I’ve created to simplify complex data science concepts. Each character represents a different aspect of data science, making learning fun and easy to understand.
Want to see a sample? Click Here
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SQL: LeetCode | HackerRank | Mode Analytics | SQLZoo | W3Schools SQL Tryit Editor
Python: LeetCode | HackerRank | Codecademy | Replit | Google Colab
Click to Discover Top and Upcoming Content Creators in Data Science
Top Platforms:
Virtual Internship: Forage
Internship: Internshala(How to optimize) | Unstop(How to optimize)
Note: These platforms offer both internships and jobs, although some are more focused on internships, while others are geared towards job opportunities.
Events:
Competition: FP20 Analytics, Onyx, Codebasics
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