Data Science for the Technical Leader

Course Description

Designed for scientists and engineers in technical leadership positions, this course provides an immersive introduction to data science and data management concepts for data-driven organizations. Through lectures, hands-on exercises, and project assignments, the course walks students through the full data science ecosystem: data management and wrangling, AI and machine learning methods, statistical fundamentals, commercial AI/ML tooling, solution deployment, and result evaluation. Students will learn the terminology and skills necessary to effectively lead the teams and processes behind data-driven work — from problem formulation and project design through operational delivery. Policy, governance, and the ethical dimensions of Data Science and AI round out the curriculum, equipping leaders to make decisions that are not only technically sound but organizationally defensible.This course explores the use of emerging AI technologies, such as Generative AI, throughout the data science process. Although there is a temptation to rely on Generative AI as a primary analytical tool, effective use of these capabilities depends on a working understanding of the data science and data engineering fundamentals underneath them. Leaders who have developed that foundation are better positioned to validate AI-enabled results, recognize the influence of data quality on outputs, and exercise the independent judgment needed to determine when those results can be trusted.Familiarity with desktop operating systems and software is required. Only basic coding familiarity is needed, as the emphasis throughout is on leadership judgment, critical evaluation, and decision-making across the AI and data science process.

Code

EN.595.758

Credits

3

Subject

Engineering Management

Programs That Include This Course

• Master's Engineering Management, Master of Engineering Management