Introduction to Data Science

This hands‑on course introduces students to the foundational concepts, techniques, and workflows that drive modern data science.

Learners will explore the complete data science process, including defining project goals, acquiring and preparing data, conducting exploratory analysis, and applying introductory machine‑learning methods.

The curriculum provides an overview of essential mathematics and statistics for data science and offers practical experience with Python, SQL, and the R programming language.

Students will practice documenting analytical workflows, clearly articulating project objectives, gathering and cleaning data, and applying core data‑munging techniques.

Through guided exercises, they will use R to perform exploratory data analysis, create effective visualizations, and implement both supervised and unsupervised learning algorithms in business‑focused scenarios.

By the end of the course, learners will understand how data science projects are structured, how to communicate analytical goals with clarity, and how to apply foundational programming and modeling techniques to real‑world problems using R, Python, and SQL.