Intro to Data for Data Science
Requirements
- None - this is an introductory course for beginners
In an information economy, data is the new oil. However, most people lack even a basic understanding of what data are and how they are used in data science. As a result, many of us will be left behind during the next industrial revolution, an information revolution.
In this course, we will learn about data as a foundation for data science. We’ll learn what data are and why they are important. In addition, we’ll learn about data types, data structures, tabular data, and the data life cycle.
By the end of this course, you’ll understand data and how data are used in data science.
- Beginners
- IT Professionals
- Introduction
- The Rise of Data
- Course Overview
- Overview
- Data
- Information
- Knowledge
- Purpose
- Process
- Summary
- Overview
- Types of Data
- Nominal Data
- Ordinal Data
- Interval Data
- Ratio Data
- Summary
- Overview
- Data Types
- Scalar Data Types
- Scalar Data Type Examples
- Composite Data Types
- Composite Data Type Examples
- Summary
- Overview
- Tabular Data
- Observations
- Variables
- Relationships
- Queries
- Summary
- Overview
- Collection
- Storage
- Processing
- Analysis
- Action
- Repeat
- Summary
- Next Steps
- Summary
- Quiz
![Matthew Renze](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.2 Instructor Rating
- 44 Reviews
- 3,686 Students
- 1 Course
Matthew Renze is a data science consultant, author, and public speaker. Over the past two decades, he has taught over 250,000 software developers and IT professionals how to build intelligent software systems. His clients include small software start-ups to Fortune 100 companies across the globe.
He’s a Microsoft MVP, an ASPInsider, an author for Pluralsight, and an open-source software contributor. His focus includes artificial intelligence, machine learning, and data