Über diesen Kurs

41,013 kürzliche Aufrufe

Nearly every aspect of business is affected by data analytics. There are many powerful tools that can quickly process large amounts of data. For businesses to capitalize on data analytics, they need leaders who understand the data analytic process. Even more valuable are leaders who know how to analyze big data. This course addresses the human skills gap by providing a foundational set of data analytic skills that can be applied to many business settings.

Zertifikat zur Vorlage

Erhalten Sie nach Abschluss ein Zertifikat

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Ca. 15 Stunden zum Abschließen

Englisch

Untertitel: Englisch

Kompetenzen, die Sie erwerben

Business AnalyticsR ProgrammingRstudio

Zertifikat zur Vorlage

Erhalten Sie nach Abschluss ein Zertifikat

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Ca. 15 Stunden zum Abschließen

Englisch

Untertitel: Englisch

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche

1

Woche 1

4 Stunden zum Abschließen

Course Overview and Module 1 Introduction to Business Analytics and R

In this module you will be introduced to the role of data analytics in business domains.

4 Stunden zum Abschließen

18 Videos (Gesamt 112 min), 5 Lektüren, 2 Quiz

18 Videos

Course Introduction2m

Meet Prof Ron Guymon2m

Meet Prof Ashish Khandelwal50

Introduction to Business Analytics and R6m

Lesson 1-1.1: Overview of Business Analytics3m

Lesson 1-1.2: Examples of Business Analytics5m

Lesson 1-1.3: FACT Framework7m

Lesson 1-2.1: Introduction to R6m

Lesson 1-2.2: Getting Started with R5m

Lesson 1-2.3: Calculations with R12m

Lesson 1-2.4: Making Your Code Readable4m

Lesson 1-3.1: Functions and Using the Built-In Help8m

Lesson 1-3.2: Reading and Writing Data12m

Lesson 1-3.3: Getting to Know Your Data 14m

Lesson 1-3.4: Getting to Know Your Data 27m

Lesson 1-3.5: Getting to Know Your Data 35m

Lesson 1-3.6: Introduction to Other Data Types12m

Module 1 Conclusion1m

5 Lektüren

Syllabus10m

About the Discussion Forums10m

Glossary10m

Module 1 Overview10m

Module 1 Readings1h

2 praktische Übungen

Orientation Quiz

Module 1 Quiz30m

Woche

2

Woche 2

3 Stunden zum Abschließen

Module 2 Assembling Data

In this module you'll identify how framing a question and the intended analysis influence the way in which data is assembled.

3 Stunden zum Abschließen

14 Videos (Gesamt 111 min), 2 Lektüren, 1 Quiz

14 Videos

Introduction to Module 2: Assembling Data5m

Lesson 2-1.1: Framing a Question6m

Lesson 2-1.2: Assembling Data7m

Lesson 2-1.3: Calculate the Results9m

Lesson 2-2.1: Data Types6m

Lesson 2-2.2: Packages9m

Lesson 2-2.3: Creating Date Types8m

Lesson 2-2.4: Calculations with Dates9m

Lesson 2-2.5: Factors9m

Lesson 2-2.6: Logical Type and Relational Operators11m

Lesson 2-3.1: Conditional Statements7m

Lesson 2-3.2: Stacking Data7m

Lesson 2-3.3: Loops8m

Module 2 Conclusion1m

2 Lektüren

Module 2 Overview10m

Module 2 Readings10m

1 praktische Übung

Module 2 Quiz30m

Woche

3

Woche 3

4 Stunden zum Abschließen

Module 3 Data Quality and Data Transformation

This module starts with a discussion on the importance of Data Quality in business analytics. Later, we learn Data Transformation using Tidyverse, a group of useful R packages.

4 Stunden zum Abschließen

13 Videos (Gesamt 65 min), 2 Lektüren, 1 Quiz

13 Videos

Module 3 Introduction1m

Lesson 3-1: Data Quality4m

Lesson 3-2.1: Data Structure based on the Business Problem Part 15m

Lesson 3-2.2: Data Structure based on the Business Problem Part 25m

Lesson 3-2.3: Subset Data using Filter and Select functions5m

Lesson 3-2.4: Useful Operators for Data Manipulation5m

Lesson 3-2.5: Creating New Variables using Mutate function3m

Lesson 3-2.6: Data Aggregation using Summarize and Group_By functions5m

Lesson 3-2.7: Handling Missing Values6m

Lesson 3-2.8: Data Join8m

Lesson 3-2.9: Long vs Wide Format for Data5m

Lesson 3-2.10: Manipulating Strings7m

Module 3 Conclusion55

2 Lektüren

Module 3 Overview10m

Module 3 Readings2h

1 praktische Übung

Module 3 Quiz30m

Woche

4

Woche 4

4 Stunden zum Abschließen

Module 4 Exploratory Data Visualization using R

In this module, we will learn a powerful visualization package in ggplot2 to create useful visualizations for exploratory data analysis (EDA).

4 Stunden zum Abschließen

14 Videos (Gesamt 53 min), 2 Lektüren, 2 Quiz

14 Videos

Module 4 Introduction51

Lesson 4-1: What to Explore in the Data?2m

Lesson 4-2: Univariate and Bivariate Exploration2m

Lesson 4-3.1: Introduction to the ggplot2 Package3m

Lesson 4-3.2: Introduction to ggplot Syntax4m

Leson 4-4.1: Univariate Exploration of a Numeric Variable5m

Lesson 4-4.2: Univariate Exploration of a Categorical Variable4m

Lesson 4-5.1: Visualizing Relationship between two Numeric Variables4m

Lesson 4-5.2: Visualizing Relationship between a Numeric and a Categorical Variable5m

Lesson 4-5.3: Visualizing Relationship between two Categorical Variables5m

Lesson 4-6: Multidimensional Charts6m

Lesson 4-7: Introduction to ggplot Builder7m

Module 4 Conclusion40

Course Conclusion1m

2 Lektüren

Module 4 Overview10m

Module 4 Readings40m

1 praktische Übung

Module 4 Graded Quiz30m

Häufig gestellte Fragen

When will I have access to the lectures and assignments?
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The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?

You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Is financial aid available?

Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

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Introduction to Business Analytics with R