CODE: OG09
DURATION: 5 Days/10 Days
CERTIFICATIONS: CPD
This course is designed to introduce professionals in the oil and gas industry to the powerful capabilities of Python for data analytics and automation. Participants will learn how to harness Python to collect, clean, analyze, and visualize data while building automation workflows that streamline repetitive tasks in exploration, drilling, production, and operations. Through practical examples and industry-relevant case studies, the course bridges the gap between domain expertise and modern digital skills, empowering participants to make data-driven decisions and improve operational efficiency.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand the fundamentals of Python programming applied to oil and gas workflows.
Perform data cleaning, analysis, and visualization using libraries such as Pandas, NumPy, and Matplotlib.
Automate repetitive tasks to save time and reduce human error.
Apply Python-based analytics to solve real-world challenges in exploration, drilling, reservoir management, and production.
Integrate domain knowledge with digital skills to drive efficiency and innovation in oil and gas operations.
At the end of this course, you’ll understand:
This course is ideal for petroleum engineers, geoscientists, reservoir engineers, drilling and production engineers, data analysts, and technical professionals in the oil and gas sector who want to expand their skill set with programming and automation. It is also suitable for managers and decision-makers seeking to understand the value of data analytics and automation in optimizing operations. No prior programming experience is required, though familiarity with oil and gas workflows will be beneficial.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
4 weeks ago
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