Applying Machine Learning In O&G Industry

Applying Machine Learning In O&G Industry Course, A 14 hours hands-on training live in Basrah, Iraq

This course covers a comprehensive range of topics, including Clustering and Anomaly Detection, where participants learn about distance calculation, statistical engineering, and models such as K-Mean Clustering and Local Outlier Factor. The course also delves into Classification, exploring probability, voting mechanisms, decision boundaries, and models like KNN, Decision Tree, and Logistic Regression. In addition, the course provides in-depth training on Regression Analysis, focusing on linear regression, numerical error assessment, and advanced models like Multilinear Regression, Regression Trees, and Gradient Boosting. Finally, the course includes Time Series Analysis, addressing moving averages, data smoothing, and models such as Auto-Regression, Holt's, ETS, and ARIMA. Throughout the course, participants engage in practical projects and exercises, including production forecasting, outlier detection, ESP pump failure analysis, flow pattern analysis, and pressure drop assessment, ensuring a hands-on learning experience.