This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques. The course also provides an overview of the most common techniques used in data science, including data analysis, statistical modeling, data engineering, manipulation of data at scale (big data), algorithms for data mining, data quality, remediation and consistency operations.

Applied Learning Project

This specialization includes a capstone assignment in the fourth course that allows students to apply what they've learned about data science to a practical business scenario. This assignment requires students to evaluate a business scenario and then choose the best analytical approach that solves the stated business problem.