数据科学速成课

Part of a 5-course series, the Executive Data Science Specialization

约翰霍普金斯大学

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数据科学速成课

About this Course

By now you have definitely heard about data science and big data. In this one-week class, we 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. We’ve designed this course to be as convenient as possible without sacrificing any of the essentials.

This is a focused course designed to rapidly get you up to speed on the field of data science. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We’ve left the technical information aside so that you can focus on managing your team and moving it forward.

After completing this course you will know.

1. How to describe the role data science plays in various contexts
2. How statistics, machine learning, and software engineering play a role in data science
3. How to describe the structure of a data science project
4. Know the key terms and tools used by data scientists
5. How to identify a successful and an unsuccessful data science project
3. The role of a data science manager

Course cover image by r2hox. Creative Commons BY-SA: https://flic.kr/p/gdMuhT

数据科学速成课 is course 1 of 5 in the Executive Data Science Specialization.

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.

授课教师

Jeff Leek, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health

Brian Caffo, PhD
Professor, Biostatistics
Bloomberg School of Public Health

Roger Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health

Syllabus

Week 1 A Crash Course in Data Science

Introduction
What is Data Science?
What is statistics is good for?
What is machine learning?
What is software engineering for data science?
Structure of a data science project
The output of a data science experiment
Defining success
Data science toolbox
Separating Hype from Value

Quiz: What is data science?
Quiz: What is statistics good for?
Quiz: Machine learning
Quiz: Quiz: Software Engineering
Quiz: Structure of a Data Science Project
Quiz: The outputs of a data science experiment
Quiz: Defining Success in Data Science
Quiz: Data scientist toolbox
Quiz: Separating hype from value

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