Course overview
This course introduces the opportunities, challenges and current development of data analytics applications in oil and gas industry. The theory and fundamental equations, as well as understanding data driven methods are covered. Practical methods, real field examples will equip students to apply data analytics and machine learning methods in petroleum engineering. The course covers the following topics with specific applications in resources engineering: Overview of Data Analytic, Introduction to Programming in Python, Univariate and Multivariate Descriptive Statistics, Supervised Machine Learning, and clustering.
- Introduction & Python Fundamentals
- Supervised Learning
- Regression & Unsupervised Learning
Course learning outcomes
- Use Python basic commands and deal with specialty data types
- Apply Python Machine Learning Packages in resources engineering applications
- Describe the fundamentals of Descriptive and Predictive Analytics
- Learn how to perform regression, data clustering, feature extraction and classification
- Learn how to use basic artificial neural networks
- Choose the most appropriate ML and DA model
Availability
Class details
Adelaide City Campus East
Class number 51177
Section FR01
Size 20
Available 20
Class number 51178
Section WS01
Size 20
Available 20
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The Student Contribution amount displayed below is for students commencing a new program from 2021 onwards. If you are continuing in a program you commenced prior to 1 January 2021, or are commencing an Honours degree relating to an undergraduate degree you commenced prior to 1 January 2021, you may be charged a different Student Contribution amount from the amount displayed below. Please check the Student Contribution bands for continuing students here. If you are an international student, or a domestic student studying in a full fee paying place, and are continuing study that you commenced in 2025 or earlier, your fees will be available here before enrolments open for 2026.