Course Information

Course Name	Turkish	Jeo-Enerji Verilerinin Analitiği
	English	Geo-Energy Data Analytics
Course Code	PET 328E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Fazıl Emre Artun
Course Objectives		1.Familiarize students with subsurface data types collected in oil, natural gas and geothermal engineering 2.Develop students’ ability to apply exploratory data analysis, data mining concepts to subsurface data with appropriate visualization and analysis techniques 3.Develop students’ ability to deal with large data sets through the use of modern computational tools and packages 4.Introduce students supervised and unsupervised machine learning algorithms for the development of prediction and classification models for subsurface data
Course Description		Overview of data science concepts. Data types for subsurface energy resources. Basic principles of descriptive and inferential statistics. Exploratory data analysis and data mining as applied to subsurface data types. Data visualization. Introduction to supervised and unsupervised machine learning. Applications with modern computational tools and packages. Case studies for oil, natural gas and geothermal engineering.
Course Outcomes		1.Define and classify different types of data collected for subsurface energy resources 2.Clean and process subsurface data using modern statistical computational packages for further analysis and visualization 3.Perform exploratory data analysis by creating and interpreting visual representations and statistical summaries of data related to subsurface energy resources 4.Design and train machine learning models for prediction and classification using supervised and unsupervised algorithms 5.Report data analytics and machine learning projects in an organized way and in reproducible formats
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