This comprehensive master course covers the full data science lifecycle — from data collection through modeling and deployment. Designed for aspiring data scientists, it blends theory, statistics, machine learning, data visualization, and real-world projects. You'll learn Python-based tools like pandas, scikit-learn, and TensorFlow to develop end-to-end

pipelines.

The program offers deep insights into statistical analysis, exploratory data analysis (EDA), feature engineering, predictive modeling, and deployment techniques. You'll work on a variety of real-world datasets across domains like retail, finance, and healthcare. Practices like model tuning, validation, version control, and reproducibility are emphasized to prepare you for real-world data science roles.

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