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Full Stack Data Science & AI: Data Cleaning, Roles & ML Roadmap | Day 2
4 months ago
9
Day 2 of the Full Stack Data Science & AI Course deep-dives into core concepts! Learn:
Data science defined: Predicting outcomes from past data using ML/AI (admission/salary/sales/BMI examples)
Critical data cleaning: Handle missing values (zero-fill experience, mean-imputation test scores)
Role breakdown: Data analyst vs. engineer vs. scientist responsibilities clarified
Full learning path: Python → statistics → ML → AI (NLP/computer vision) → Azure/Flask deployment → Power BI visualization
Key insight: "Data preprocessing is 70% of data science work!" 🔧 Includes admission predictors, sentiment analysis tools & sales forecasters.
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