Game Data Science Using R

Intermediate

151 Lessons

45h

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

283 Playgrounds
11 Quizzes

This course includes

283 Playgrounds
11 Quizzes

Course Overview

Game data science is emerging as a significant field of study due to the emergence of social games embedded in online social networks. The ubiquity of social games gives access to new data sources and impacts essential business decisions, given the introduction of freemium business models. Game data science covers collecting, storing, analyzing data, and communicating insights. This course will teach you game data extraction, processing, data abstraction, data analysis through visualization, data clusterin...Show More

What You'll Learn

Ability to use machine learning applications in game data science

Hands-on experience of the R programming language in real-world applications

Ability to build solid theoretical knowledge of game data science

Learn to collect, visualize, analyze, and transform game data

Learn about data clustering, supervised learning, neural networks, and sequence analysis

What You'll Learn

Ability to use machine learning applications in game data science

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Course Content

1

Getting Started

2

Introduction to Game Data Science

3

Data Preprocessing

4

Introduction to Statistics and Probability Theory

5

Data Abstraction

6

Data Analysis through Visualization

9 Lessons

7

Clustering Methods in Game Data Science

21 Lessons

8

Supervised Learning in Game Data Science

23 Lessons

9

Model Validation and Evaluation

11 Lessons

10

Introduction to Neural Networks

10 Lessons

11

Sequence Analysis of Game Data

14 Lessons

12

Advanced Sequence Analysis

13 Lessons

13

Case Study: Tom Clancy's The Division (TCTD)

5 Lessons

14

Conclusion and Remarks

3 Lessons

15

Appendix A: Game Used in the Book

1 Lesson

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