🤖 Hands on Machine Learning for Geoscientists and Engineers

Overview

🔎 Course Description

Artificial Intelligence (AI) is rapidly transforming the energy sector — from exploration to production optimization, predictive maintenance, and business operations. This course demystifies AI for geoscientists, engineers, and managers, giving them practical knowledge and tools to understand, implement, and collaborate effectively on AI projects. The program covers the fundamentals of machine learning, key algorithms, data workflows, and AI applications tailored to oil and gas challenges.

🎯 Learning Objectives

✅ Grasp core AI and machine learning concepts
✅ Understand data types, quality issues, and feature engineering
✅ Explore supervised and unsupervised algorithms
✅ Build and evaluate simple AI models using real energy datasets
✅ Recognize AI’s potential and limitations in energy operations
✅ Communicate effectively with data science teams

👥 Who Should Attend

Engineers (reservoir, production, drilling, facilities)
Geoscientists and petrophysicists
Technical team leads and asset managers
Data analysts and IT professionals in energy companies
Anyone interested in applying AI to energy projects

🗂️ Training Format

✅ Instructor-led lectures and discussions
✅ Practical, hands-on exercises with easy-to-use AI tools (Python notebooks, web-based platforms)
✅ Case studies of AI success in oil and gas
✅ Group projects
✅ Daily Q&A sessions

📅 Detailed Daily Agenda with Time Breaks

📅 Day 1: Introduction to AI and Machine Learning Basics

Time	Topic
08:30 – 09:00	Registration & Welcome
09:00 – 10:30	What is AI? Myths & Realities in Oil & Gas
10:30 – 10:45	☕ Coffee Break
10:45 – 12:15	Data Science & Machine Learning Foundations
12:15 – 13:15	🍽 Lunch
13:15 – 14:45	Data Types & Data Quality in Energy Datasets
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	AI Project Lifecycle & Tools Overview

📅 Day 2: Preparing Data for AI

Time	Topic
08:30 – 10:00	Data Cleaning & Handling Missing Values
10:00 – 10:15	☕ Coffee Break
10:15 – 12:15	Feature Engineering: Extracting Meaningful Information
12:15 – 13:15	🍽 Lunch
13:15 – 14:45	Exploratory Data Analysis (EDA) for Energy Data
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Hands-On: EDA on Production or Drilling Data

📅 Day 3: Supervised Learning Algorithms

Time	Topic
08:30 – 10:00	Linear & Logistic Regression Explained
10:00 – 10:15	☕ Coffee Break
10:15 – 12:15	Decision Trees & Random Forests
12:15 – 13:15	🍽 Lunch
13:15 – 14:45	Model Evaluation Metrics (Accuracy, RMSE, ROC)
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Hands-On: Building a Predictive Model

📅 Day 4: Unsupervised Learning & Clustering

Time	Topic
08:30 – 10:00	Understanding Clustering & Dimensionality Reduction
10:00 – 10:15	☕ Coffee Break
10:15 – 12:15	K-Means & Hierarchical Clustering
12:15 – 13:15	🍽 Lunch
13:15 – 14:45	Principal Component Analysis (PCA)
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Hands-On: Clustering Energy Production Profiles

📅 Day 5: AI Applications & Group Project

Time	Topic
08:30 – 10:00	AI Applications in Exploration & Production
10:00 – 10:15	☕ Coffee Break
10:15 – 12:15	Ethics, Bias, & Limitations of AI
12:15 – 13:15	🍽 Lunch
13:15 – 14:45	Group Project: Design an AI Solution for a Real Challenge
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Group Presentations & Closing Discussion

📦 Materials Provided

✅ Interactive Python notebooks
✅ AI workflow templates
✅ Real oil & gas datasets
✅ Certificate of Completion

Target audiences

Reservoir Engineers, Geologists

$ 5,950

Course Features