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Intro to Data for Data Science

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Intro to Data for Data Science, available at Free, has an average rating of 4.55, with 41 lectures, 1 quizzes, based on 916 reviews, and has 16601 subscribers.

You will learn about Learn what data are and why they are important Learn how data are used in data science Learn the types of data that exist in data science Learn how data are represented in a computer Learn how to extract information from a table of data Learn about the data life-cycle from data collection to action This course is ideal for individuals who are Beginners or IT Professionals It is particularly useful for Beginners or IT Professionals.

Enroll now: Intro to Data for Data Science

Summary

Title: Intro to Data for Data Science

Price: Free

Average Rating: 4.55

Number of Lectures: 41

Number of Quizzes: 1

Number of Published Lectures: 41

Number of Published Quizzes: 1

Number of Curriculum Items: 42

Number of Published Curriculum Objects: 42

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

  • Learn what data are and why they are important
  • Learn how data are used in data science
  • Learn the types of data that exist in data science
  • Learn how data are represented in a computer
  • Learn how to extract information from a table of data
  • Learn about the data life-cycle from data collection to action

Who Should Attend

  • Beginners
  • IT Professionals

Target Audiences

  • Beginners
  • IT Professionals

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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: The Rise of Data

Lecture 3: Course Overview

Chapter 2: Data

Lecture 1: Overview

Lecture 2: Data

Lecture 3: Information

Lecture 4: Knowledge

Lecture 5: Purpose

Lecture 6: Process

Lecture 7: Summary

Chapter 3: Types of Data

Lecture 1: Overview

Lecture 2: Types of Data

Lecture 3: Nominal Data

Lecture 4: Ordinal Data

Lecture 5: Interval Data

Lecture 6: Ratio Data

Lecture 7: Summary

Chapter 4: Data Types

Lecture 1: Overview

Lecture 2: Data Types

Lecture 3: Scalar Data Types

Lecture 4: Scalar Data Type Examples

Lecture 5: Composite Data Types

Lecture 6: Composite Data Type Examples

Lecture 7: Summary

Chapter 5: Tabular Data

Lecture 1: Overview

Lecture 2: Tabular Data

Lecture 3: Observations

Lecture 4: Variables

Lecture 5: Relationships

Lecture 6: Queries

Lecture 7: Summary

Chapter 6: Life Cycle

Lecture 1: Overview

Lecture 2: Collection

Lecture 3: Storage

Lecture 4: Processing

Lecture 5: Analysis

Lecture 6: Action

Lecture 7: Repeat

Lecture 8: Summary

Chapter 7: Conclusion

Lecture 1: Next Steps

Lecture 2: Summary

Instructors

Rating Distribution

  • 1 stars: 11 votes
  • 2 stars: 18 votes
  • 3 stars: 103 votes
  • 4 stars: 299 votes
  • 5 stars: 485 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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