Data science track par aane ke liye aapko har ek library ya syntax ko rą¤ą¤Øą„ ki zaroorat nahi hai. Real-world engineering me focus hamesha problem-solving par hota hai, na ki syntax par.
Agar aap short and straight path dhoond rahe hain, toh sirf is minimal stack ko master kar lo:
Python Syntax: Focus on loops, list comprehensions, and functions.
Data Wrangling: Master Pandas and NumPy. Datasets ko clean karna hi aapka 80% real job work hota hai.
SQL: Relational databases se data fetch karne ke liye mandatory tool hai. Do not skip this!
Modeling: Learn Scikit-learn for baseline machine learning models.
The Practical Hack:
Don't get trapped in tutorial hell. Shrestha Academy me humne notice kiya hai ki jo log theoretical lectures dekhne ke bajaye daily 30-45 minutes core fundamentals aur datasets ko practically code karte hain, wo apna portfolio 2x tez build kar lete hain.
Aapko certificates se zyada apne GitHub portfolio par focus karna chahiye.
If you want the complete, zero-fluff step-by-step blueprint with actual tool timelines, check out the comprehensive guide by Shrestha Academy on how to become a data scientist with python.
Let's build something practical today! š»
Top comments (0)