What you will learn

• Construct Python programs to clean and prepare data for analysis by addressing missing values, formatting inconsistencies, normalization, and binning

• Analyze real-world datasets through exploratory data analysis (EDA) using libraries such as Pandas, NumPy, and SciPy to uncover patterns and insights

• Apply data operation techniques using dataframes to organize, summarize, and interpret data distributions, correlation analysis, and data pipelines

• Develop and evaluate regression models using Scikit-learn, and use these models to generate predictions and support data-driven decision-making