The digital learning ecosystem An efficient management approach to capability development, delivering smarter teams, improved productivity and better business outcome for the managers.
The digital learning ecosystem Digitally and seamlessly connecting you, the learner, with pertinent learning objects and related technologies ensuring systematic, engaging and continued learning.
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Best Outreach Program Finalist: WorldOil Awards
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Training provider of the year: 2013, 14 and 15
Upstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.Engaging. Educational. Enjoyable
Develop measurable skills and capabilities
Interest in data science and machine learning is rapidly expanding, offering the promise of increased efficiency in E&P, and holding the potential to analyze and extract value from vast amounts of under-utilized legacy data.
Combined with petroleum geoscience and engineering domain knowledge, the key elements underlying the successful application of the technology are: data, code, and algorithms. This course builds on public datasets, code examples written in Python, and algorithms from popular data science packages to provide a practical introduction to the subject and its application in the E&P domain.This course will delivered entirely online, for 4 hours each day.
Data Science Toolkit - Notebooks, Visualization, and Communication (2hr)
Computational Thinking (1hr)
Python Fundamentals (2hr)
Exploratory Data Analysis (2hr)
Exploring E&P Data (4hr)
Machine Learning Fundamentals (4hr)
This is an introductory course for reservoir geologists, reservoir geophysicists, reservoir engineers, and technical staff who want to learn the key concepts of data science.
No prior experience of statistics, coding or machine learning is required, although knowledge of basic maths and statistics is useful.
Hands-on computer workshops form a significant part of this course, and participants must come equipped with a laptop computer running Windows (7, 8, 10) or MacOS (10.10 or above) with sufficient free storage (4 Gb).
Customize your own learning journey and track your progress when you start using a defined learning path.