INTERACTIVE COURSE

Intermediate

151 Lessons

45h

Certificate of Completion

AI Explanations

AI Explanations

283 Playgrounds

11 Quizzes

241 Illustrations

Takeaway Skills

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

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...

Course Content

1

Getting Started

2

Introduction to Game Data Science

Game AnalyticsWhat is Game Data?Historical Context for Game Data ScienceEra of Game Data and Machine LearningThe Process of Game Data ScienceWhat are Metrics in Game Data Science?Introduction to Customer MetricsIntroduction to Gameplay MetricsKey Performance IndicatorsImportance of Metrics to Game Data ScienceSummary: Basics of Game Data ScienceQuiz on Basics of Game Data Science

3

Data Preprocessing

About This ChapterWhat is Data Preprocessing?Data Example and Measurement TypesProcess for PreprocessingReading and Parsing FilesPurpose of Cleaning and Data Type ChecksData Consistency ProcessingData Normalization and StandardizationSummary: Data reprocessingQuiz on Preprocessing of Data

4

Introduction to Statistics and Probability Theory

Introduction to Probability and StatisticsMeasures of CentralityMeasure of SpreadIntroduction to Correlation AnalysisIntroduction to Inferential StatisticsT-tests and its TypesIntroduction to Analysis of Variance (ANOVA)Introduction to ProbabilitySummary: Statistics and Probability TheoryQuiz on Statistics and Probability Theory

5

Data Abstraction

Significance of Behavioral TelemetryIntroduction to DatasetIntroduction to Feature ExtractionHow to Deal with Nominal and Ordinal Measures?The Process of Feature SelectionIntroduction to EntropySummary: Data AbstractionQuiz on 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

COURSE AUTHOR

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