OpenCourser brand icon
Sign in
We may earn an affiliate commission when you visit our partners.

Data Science in the Games Industry

Andy Cobley, Mark Whitehorn, Patrick Blackwill, Stuart Anderson, Alex Taylor, Iain Kay, Gary Bowerbank, and James Frost

Week 1: Data in all its glory Week 2: Breaking the CAP Triangle Week 3: Taming the Data Exhaust Week 4: Analysis is our answer Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more 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. You can use the hashtag #FLgamingdata to talk about this course on social media.

Topics Covered

Read more

Week 1: Data in all its glory Week 2: Breaking the CAP Triangle Week 3: Taming the Data Exhaust Week 4: Analysis is our answer Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more 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. You can use the hashtag #FLgamingdata to talk about this course on social media.

Topics Covered

  • The Data Exhaust
  • Tabular vs Big Data
  • Disappearances in the CAP Triangle
  • NoSQL
  • Cassandra
  • MongoDb
  • Graphs and Graph Databases
  • Dark Data’s Hiding Place
  • Big Data and Distributed Systems
  • Hadoop, HDFS, MapReduce and Other Technologies
  • Real-time Systems
  • Lambda
  • Introduction to Statistics
  • Consumer Testing
  • Introduction to R and Python
  • Bayesian Statistics
  • Machine learning and data mining
  • The Future of Data Science
Enroll now

Save this course

Save Data Science in the Games Industry to your list so you can find it easily later:
Save

Activities

Coming soon We're preparing activities for Data Science in the Games Industry. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Data Science in the Games Industry will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.
Cover image
Data Analysis
Save
An excellent overview of Bayesian statistics, this book provides a comprehensive introduction to the theory and practice of Bayesian data analysis. The focus on practical applications and real-life examples makes it a great choice for students and practitioners alike.
Data Analysis: A Bayesian Tutorial
Paperback
$$
Data Analysis: A Bayesian Tutorial
Kindle Edition
$$
Cover image
Data Mining
Save
A classic text in the field of data mining, this book provides a comprehensive overview of techniques and algorithms used for extracting knowledge from large datasets. Written by leading experts in the field, it valuable resource for students and researchers.
Data Mining: Practical Machine Learning Tools and...
Paperback
$$$
DATA MINING, 4TH EDITION
Paperback
$$
Data Mining: Practical Machine Learning Tools and...
Kindle Edition
$$
Cover image
Python for Data Analysis
Save
A hands-on guide to data analysis using Python, this book covers a wide range of topics, including data cleaning, transformation, visualization, and modeling. Written by the creator of Pandas, it practical resource for students and professionals in various fields.
Python for Data Analysis: Data Wrangling with...
Paperback
$$
Python for Data Analysis
Kindle Edition
$$
Cover image
An Introduction to Statistical Learning
Save
An authoritative text on statistical learning, this book covers a wide range of topics, including linear and nonlinear regression, classification, unsupervised learning, and model selection. It comprehensive resource for students and practitioners in various fields.
An Introduction to Statistical Learning
Paperback
Check
An Introduction to Statistical Learning
Kindle Edition
Check
Cover image
Python Machine Learning
Save
This online book provides a comprehensive overview of machine learning concepts and techniques. Written by a leading expert in the field, it valuable resource for students and practitioners who want to gain a deep understanding of machine learning.
Python Machine Learning
Paperback
Check
Python Machine Learning
Kindle Edition
Check
Cover image
R for Data Science
Save
A comprehensive introduction to data analysis using R, this book covers a wide range of topics, including data manipulation, visualization, and statistical modeling. Written by leading experts in the field, it valuable resource for students and practitioners.
R for Data Science
Paperback
Check
R for Data Science
Kindle Edition
Check
Cover image
Statistical Data Analysis
Save
Provides a comprehensive overview of statistical methods for data analysis, covering topics such as probability distributions, hypothesis testing, and regression analysis. Written by a leading expert in the field, it valuable resource for students and practitioners in various fields.
Statistical Data Analysis
Paperback
Check
Statistical Data Analysis
Kindle Edition
Check
Cover image
The Data Science Handbook
Save
This comprehensive handbook provides a wide range of topics in data science, including data mining, machine learning, and data visualization. Written by experts in the field, it valuable resource for students and practitioners who want to gain a broad understanding of data science.
The Data Science Handbook: Advice and Insights from...
Paperback
$$
Cover image
The Elements of Statistical Learning
Save
A classic text in the field of statistical learning, this book covers a wide range of topics, including linear and nonlinear regression, classification, unsupervised learning, and model selection. It comprehensive resource for students and practitioners in various fields.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
Understanding Machine Learning
Save
Provides a comprehensive overview of machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. Written by leading experts in the field, it valuable resource for students and practitioners who want to gain a deep understanding of machine learning.
Understanding Machine Learning: From Theory to...
Hardcover
$$$
Understanding Machine Learning: From Theory to...
Kindle Edition
$$
Cover image
Data Science for Business
Save
Provides a practical introduction to data science for business professionals. It covers topics such as data mining, data visualization, and statistical modeling. Written by experts in the field, it valuable resource for anyone who wants to gain a better understanding of data science.
Data Science for Business: What You Need to Know...
Paperback
$$
Data Science for Business: What You Need to Know...
Kindle Edition
$$
Cover image
Analytics in a Big Data World
Save
Provides a comprehensive overview of big data analytics, covering topics such as data management, data mining, and data visualization. It valuable resource for students and practitioners who want to gain a better understanding of big data analytics.
Analytics in a Big Data World: The Essential Guide...
Hardcover
$$
By Bart Baesens Analytics in a Big Data World: The...
Hardcover
$$$
Analytics in a Big Data World: The Essential Guide...
Kindle Edition
$$
Cover image
Python Machine Learning
Save
This book, written by the Stanford University professor and former Chief Scientist at Baidu, provides a clear overview of machine learning with lots of diagrams and hands-on practice.
Python Machine Learning: The Ultimate Guide for...
Paperback
$$$$
Machine Learning: The Most Complete Guide for...
Paperback
$$
Data Science and Big Data Analytics: A Step by Step...
Paperback
$
Python Programming: Learn Python with the Most...
Paperback
$$$
Machine Learning: The Ultimate Guide for Beginners...
Hardcover
$$$$
Python Data Science: An Essential Guide for...
Hardcover
$
Cover image
Dive into Deep Learning
Save
Provides a comprehensive and practical guide to deep learning, including hands-on exercises and real-world examples.
Dive into Deep Learning
Paperback
$$
Cover image
Pattern Recognition and Machine Learning
Save
Classic text on machine learning and statistical pattern recognition, with a focus on Bayesian approaches. The author has won the prestigious Turing Award.
Pattern Recognition and Machine Learning...
Hardcover
$$$
Pattern Recognition and Machine Learning...
Paperback
$$$
Pattern Recognition and Machine Learning (text...
Unknown Binding
$$$$
Cover image
An Introduction to Statistical Learning
Save
Provides a balanced treatment of both statistical and machine learning methods, making it accessible to a wide audience.
An Introduction to Statistical Learning
Paperback
Check
An Introduction to Statistical Learning
Kindle Edition
Check
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Practical guide to machine learning with Python, covering a wide range of topics from data preprocessing to model evaluation.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Machine Learning for Absolute Beginners
Save
Gentle introduction to machine learning, suitable for those with no prior knowledge of the field, with a focus on understanding the concepts rather than the math.
Machine Learning for Absolute Beginners: A Plain...
Paperback
$$
Data Analytics for Absolute Beginners: A...
Paperback
$$
Machine Learning For Absolute Beginners: A Plain...
Paperback
$$
Machine Learning for Absolute Beginners: A Plain...
Paperback
$$
Machine Learning for Absolute Beginners: A Plain...
Kindle Edition
$
Cover image
Machine Learning
Save
Provides a comprehensive treatment of machine learning from a probabilistic perspective, covering a wide range of topics from Bayesian inference to deep learning.
Machine Learning
Paperback
Check
Machine Learning
Kindle Edition
Check
Cover image
Machine Learning for Hackers
Save
Practical guide to machine learning for programmers, with a focus on using Python to build and deploy machine learning models.
Machine Learning for Hackers: Case Studies and...
Paperback
$$
Machine Learning for Hackers: Case Studies and...
Kindle Edition
$$

Share

Help others find this course page by sharing it with your friends and followers:
Facebook
LinkedIn
Reddit
X
Link
Email

Similar courses

Similar courses are unavailable at this time. Please try again later.
Via
FutureLearn
Institution
University of Dundee
Instructors
Andy Cobley
Mark Whitehorn
Patrick Blackwill
Stuart Anderson
Alex Taylor
Iain Kay
Gary Bowerbank
James Frost
Share and help others discover this course.
Facebook LinkedIn X Reddit Link Email
Don't miss out
Enroll today to gain access to this course
Enroll in this course
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser