Master data analysis, visualisation and the basics of Machine Learning. From data preparation to building predictive models, with a hands-on project.
Overview of data jobs, project life cycle and the CRISP-DM methodology.
Essential Python refresher and working environment.
NumPy: arrays, vector operations and efficient computation.
Pandas: DataFrames, indexing, filtering and aggregations.
Handling missing values, duplicates, outliers and encoding variables.
Transformation and feature engineering.
Matplotlib and Seaborn: advanced charts and storytelling.
Complete exploratory data analysis (EDA).
Train/test split, model evaluation, regression and classification.
Complete project: building, training, evaluating and presenting.
Ready to turn data into insights?