Data Science in the Games Industry

Learn how the games industry can use big data to enhance the gaming experience and increase profits.

Use data analysis to build better gaming experiences

The video games industry collects vast amounts of data from its users. But most of this data is disregarded despite its value to the gaming industry.

This course will show you how to store and analyse data effectively and gain insights into game users’ actions and behaviours.

You’ll find out about the different models of data, such as tabular data, atomic data, and relational data.

You’ll understand how to store non-relational data at scale, and why data can be hard to distribute.

You’ll learn how to build better gaming experiences and increase profits.

What topics will you cover?

Week 1: Data in all its glory

  • The Data Exhaust
  • Tabular vs Big Data
  • Disappearances in the CAP Triangle

Week 2: Breaking the CAP Triangle

  • NoSQL
  • Cassandra
  • MongoDb
  • Graphs and Graph Databases
  • Dark Data’s Hiding Place

Week 3: Taming the Data Exhaust

  • Big Data and Distributed Systems
  • Hadoop, HDFS, MapReduce and Other Technologies
  • Real-time Systems
  • Lambda

Week 4: Analysis is our answer

  • Introduction to Statistics
  • Consumer Testing
  • Introduction to R and Python
  • Bayesian Statistics
  • Machine learning and data mining
  • The Future of Data Science

Who is the course for?

This course is aimed at those who already work in the games industry, but may also be of interest to those looking to work in the sector.

What software or tools do you need?

In order to get the best out of this course, you should have a laptop or desktop computer (Windows or Mac) that can run virtual machine software such as VirtualBox or Docker. You should be happy to install software on your machines such as Python or R Studio. Links and instructions for installation and use will be included during the course.

Data Science in the Games Industry

Originally posted 2022-03-02 01:13:54.


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