A Crash Course in Data Science

A Crash Course in Data Science

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 th

UTM Shillong Admission 2017
Punjab MBBS / BDS Admission 2017 – Baba Farid University MBBS Admission
CMAT Rajasthan Counselling 2017

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

WEEK 1
A Crash Course in Data Science

 

11 videos, 8 readings

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

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