Data Science W201

Research Design and Applications for Data and Analysis

3 units

Course Description

Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. 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. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make.

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

Skill Sets

Research design / Question formulation / Data and decision making / Understanding cognitive bias / Data for persuasion and action / Integrating data and domain knowledge / Storytelling with data

Current Course Designers

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Steven Weber
Steven Weber
Professor of the Graduate School

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Mike Rivera
Michael Rivera
Assistant Professor of Practice
5 South Hall (Office hours held online)

Original Course Designers

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Steven Weber
Steven Weber
Professor of the Graduate School

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Andy Brooks
Alumni (PhD 2017) Alumni (MIMS 2010)

Prerequisites

MIDS students only.

Video

datascience@berkeley | Research Design and Application for Data and Analysis

datascience@berkeley | Research Design and Application for Data and Analysis

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Course Spotlight

MIDS Course Spotlight: Data Science W201 (July 17, 2020)

Course History

Summer 2022

Instructor(s): Elena Petrov
Instructor(s): Carlos Rivera
Instructor(s): Anna Zaitsev
Instructor(s): Anna Zaitsev
Instructor(s): Sahab Aslam
Instructor(s): Carlos Rivera
Instructor(s): Brooks Ambrose
Instructor(s): Conor Healy
Instructor(s): JP Dolphin

Spring 2022

Instructor(s): Elena Petrov
Instructor(s): Michael Rivera
Instructor(s): Michael Rivera
Instructor(s): Brooks Ambrose
Instructor(s): Brooks Ambrose
Instructor(s): Conor Healy

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Last updated:

June 18, 2021