Applied Machine Learning And Data Science For Upstream Professionals
June 20 - June 24
Why Choose this Training Course
This highly practical 5-day course aims to provide upstream professionals with a comprehensive introduction to the main machine learning methods and builds hands-on experience in data science and machine learning.
Through the course, you will develop a solid understanding of supervised and unsupervised learning algorithms including advanced topics such as deep learning and machine learning models explainability.
The course is designed to build up your confidence from scratch: starting with an introduction of each method in simple terms, followed by detailed guidelines on how to apply different machine learning methods for solving actual problems from reservoir engineering, geo-modelling, and petrophysics. The knowledge obtained from the course – in combination with carefully designed code examples – can be applied by the participants in ongoing and future projects, thus increasing their overall performance.
Who Should Attend
A reservoir engineer, geologist or petrophysicist, and keen to obtain a fundamental understanding and practical knowledge on data science and machine learning.
– Participants should have strong upstream domain knowledge with a minimum of 5 years experience.
– Prior scientific programming experience (Python, Pandas, SQL) or completed course “Practical Python Programming for Upstream Professionals”
Key Learning Objectives
- Understand the main machine learning methods
- Builds hands-on experience in data science and machine learning
- Develop a solid understanding of supervised and unsupervised learning algorithms
- Apply different machine learning methods for solving actual problems