data-science
This repository documents a self-directed 23-month sabbatical dedicated to mastering theoretical and applied data science through an open online university approach. It serves as a comprehensive portfolio combining handwritten notes with hands-on implementations across the full data science lifecycle. Key sections cover machine learning concepts and projects, deep learning applications, real-world case studies utilizing analyst skills, data engineering, and MLOps pipelines. The collection also includes business intelligence projects using industry-standard tools, alongside foundational mathematics implementations in probability, statistics, and linear algebra. Designed for execution in Jupyter Notebooks within an Anaconda environment, the resources offer practical exposure to core competencies required for a Master's level education. The repository tracks progress through detailed commit histories and includes solved numerical problems in PDF format. While originally a personal learning log, it invites commun