Research Design and Applications for Data and Analysis

This course introduces students to the data sciences landscape, focusing on learning how to apply data science techniques to uncover, enrich, and answer the questions you will encounter and originate in the industry. After an introduction to data science and an overview of the course, students will explore decision-making in organizations and big data’s emerging role in guiding tactical and strategic decisions. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences in ways that change minds and behaviors.

Previously listed as DATASCI W201.

Course must be taken for a letter grade to fulfill degree requirements.

Student Learning Outcomes

• Design a data science project that follows best-practice research design principles.
• Design effective research questions that lead to actionable insight and strategic decisions.
• Develop a strategy to communicate data-driven insight.
• Develop data collection methods for specific outcomes.
• Evaluate risks in data science projects related to scientific validity, stakeholder expectations, and law and ethics.
• Justify an analytical approach to inform efficient and effective decision-making.
• Justify the role and importance of data science in organizations.

Current Course Designers

Steven Weber

Professor of the Graduate School

stevew@ischool.berkeley.edu

(510) 643-3755

Michael Rivera

Assistant Professor of Practice

michaelrivera@ischool.berkeley.edu

305B South Hall

Original Course Designers

Steven Weber

Professor of the Graduate School

stevew@ischool.berkeley.edu

(510) 643-3755

Andy Brooks

Alumni (PhD 2017)
Alumni (MIMS 2010)

andy@ischool.berkeley.edu

Website