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Executive Data Science

Roger D. Peng, PhD, Jeff Leek, PhD, and Brian Caffo, PhD

Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.

In four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.

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What's inside

Five courses

A Crash Course in Data Science

(0 hours)

By now you have definitely heard about data science and big data. This one-week class will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff.

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Building a Data Science Team

(0 hours)

Data science is a team sport. As a data science executive, it is your job to recruit, organize, and manage the team to success. In this one-week course, we will cover how to find the right people to fill out your data science team, how to organize them to give them the best chance to feel empowered and successful, and how to manage your team as it grows.

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Managing Data Analysis

(0 hours)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication.

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Data Science in Real Life

(0 hours)

Have you ever had the perfect data science experience? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses.

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Executive Data Science Capstone

(0 hours)

The Executive Data Science Capstone is an opportunity to apply what you've learned to a real-world scenario. You will lead a virtual data science team and make key decisions along the way. For the final project, you will prepare and submit a presentation.

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Learning objectives

Become conversant in the field and understand your role as a leader.
Recruit, assemble, evaluate, and develop a team with complementary skill sets and roles.

Navigate the structure of the data science pipeline by understanding the goals of each stage and keeping your team on target throughout.
Overcome the common challenges that frequently derail data science projects.

Become conversant in the field and understand your role as a leader.
Recruit, assemble, evaluate, and develop a team with complementary skill sets and roles.
Navigate the structure of the data science pipeline by understanding the goals of each stage and keeping your team on target throughout.
Overcome the common challenges that frequently derail data science projects.

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Time

0 hours

Level

Introductory

Via

Coursera

Institution

Johns Hopkins University

Instructors

Roger D. Peng, PhD

Jeff Leek, PhD

Brian Caffo, PhD

Level

Introductory

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