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Intellegent Data Analytics in Petroleum Engineering

This extensive course provides a fast-paced comprehensive discussion on the fundamentals of intelligent data analyses to help students and professionals with developing a clear understanding of the concepts, definitions, methods, and the applications in the oil and gas industry.

Course Start Date: March 1, 2026
Fees: $890
View Discount and Referral Programs

Course Highlights

• Duration: Two weeks
• Full access to 16 hours of lecture videos
• Full access to lecture notes
• Solved practical examples

• Live question and answer sessions
• Three months extended access to course materials and videos
• Certificate and 16 PDH credits
• Max. capacity: 12 participants

Certificate

Certificates will be awarded to the participants upon successful completion of the course requirements and passing the course exam. The certificate includes 16 PDH credits.

Practical Examples

Practical examples in petroleum engineering will be covered by our course instructor, therefore, participants will acquire hands-on experience on real case projects.

Tools Used

• Open-source R 
• RStudio
- Statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing

Course Instructor

SHADI SALAHSHOOR, Ph.D.
Reservoir Engineer and Data Scientist at Gas Technology Institute (GTI)

Dr. Shadi Salahshoor is currently engaged in developing advanced technologies and asset management strategies for unconventional formations at GTI. She is a reservoir engineer by background with extensive experience in reservoir evaluation, characterization and modeling including the application of machine learning (ML)/artificial intelligence (AI) and cloud computing.

Course Outline

• Introduction to data science and data analytics
• Terminology and fundamental concepts
• Principles of data-driven modeling
• Statistical learning
• Machine learning models
• Model selection strategies and modeling steps
• Assessing model performance
• Feature selection and ranking
• Data-driven storytelling and decision-making workflow
• Modern intelligent data analytics in the Oil & Gas Industry
• Introduction to R
• Hands-on examples in RStudio
     – Introduction to basic functions and libraries
     – Design and develop a Machine Learning project in R
     – Create high-quality data visualizations