Machine learning is a subfield of Artificial Intelligence that acts as a bridge between Data Science and Artificial Intelligence. Its objective is to understand the structure of data and to build data-driven models for further automate decision-making processes, in most technical domains including the O&G industry.
Public :
The course is intended for O&G professionals interested in machine learning and its applications to O&G.
Level :Awareness
Prerequisite :
No pre-requisistes are necessary to follow this course.
Course Content
INTRODUCTION TO MACHINE LEARNING
MACHINE LEARNING METHODS
Supervised machine learning.
Unsupervised machine learning.
COMMON ALGORITHMIC APPROACHES
Decision tree, K nearest neighbors, deep learning.
PROGRAMMING LANGUAGES
Python, Java, R, C++.
EVALUATING MACHINE LEARNING MODELS
Quantify errors; testing and validation.
EXAMPLES OF MACHINE LEARNING APPLICATIONS IN O&G
Learning Objectives
Attendees will be able to implement the following skills:
describe the different types of machine learning, algorithms, techniques and models,
identify the main programming languages used in machine learning,
examine some machine learning applications in the O&G industry.
Ways & Means
Interactive lectures and exercises.
More
Coordinator :IFP Training instructors, with expertise in the field and trained in modern teaching methods adapted to the specific needs of learners from the professional world.
To French entities : IFP Training is referenced to DataDock ; you may contact your OPCO about potential funding.
Please contact our disabled persons referent to check the accessibility of this training program : referent.handicap@ifptraining.com
IFPT Account
