Course description

Practical Data Science & Machine Learning Foundations is a hands-on, engineering-focused course designed to bridge the gap between raw data and predictive code. Students will master the complete data pipeline from cleaning messy, real-world datasets and engineering high-impact features to building, tuning, and evaluating classical machine learning models. 

Using industry-standard Python libraries like NumPy, Pandas, and Scikit-Learn, this course equips students with the foundational skills needed to solve complex business problems with data-driven code.

What will i learn?

• Clean and transform messy, real-world datasets.
• Build and train supervised regression and classification models.
• Optimize model accuracy via hyperparameter tuning.

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