Data Science and Machine Learning — A Practical Introduction
Who it is for: analysts and developers who can use pandas and want to build models that predict, classify and segment — and know when not to trust them.
Follows the arc of leading introductory machine-learning courses (supervised learning, model evaluation, unsupervised learning, practical advice) with business datasets: customer churn, demand forecasting and lead scoring.
Prerequisite: our NumPy and pandas course.
Community and help: every enrolled student gets the course Forum tab — ask the BOSS Pacific team or other students, share fixes and lab results. Read the BP Academy blog for updates and worked examples.
Includes: the full course as a licensed PDF workbook, available after purchase.
Hands-on labs: rent a ready environment from BOSS Pacific — Docker sandbox, PostgreSQL sandbox. Every lab resets every 24 hours and is removed at the end of your rental. Or build your own with the gear listed in the course.