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    • Class and Course
    1. NExT
    2. Artificial Intelligence
    3. Practical AI Fundamentals for Energy Professionals

    Practical AI Fundamentals for Energy Professionals

    • Foundation
    • classroom1Classroom
      • Average client rating (based on 4 attendee reviews)
    Day 1

    Morning

    1. Course Introduction and Logistics
      • Overview tools, and expectations
    2. Foundations of Data Science and AI in the Energy Industry
      • Why AI/ML matters for energy professionals
      • Key developments in AI (including Generative AI overview)
      • Examples of ML/AI applications in Geoscience & Engineering
    3. Introduction to Python for Data Science
      • Basic Python syntax
      • NumPy and Pandas essentials
      • Short introduction to visualization libraries (e.g., matplotlib/Seaborn)

    Afternoon

    1. Data Wrangling and Exploratory Data Analysis (EDA) for AI/ML projects
      • Data cleaning (handling missing values, outliers)
      • Feature engineering basics
    2. Hands - on Session:
      • Basic Python/EDA Exercises (e.g., reading, cleaning and visualization of well logs)

    Day 2

    Morning

    1. Machine Learning Fundamentals
      • Supervised vs. Unsupervised Learning
      • Training/validation/test splits
      • Underfitting vs Overfitting, learning curves
    2. Regression & Classification Essentials
      • Common ML algorithms (linear regression, decision trees, etc.)
      • Regression metrics (MSE, MAE, R2R^2R2, etc.)
      • Classification metrics (accuracy, precision, recall, F1 score)

    Afternoon

    1. Hands - on Session: Regression & Classification
      • Predicting Cumulative Gas Production (Regression)
      • Facies Classification (Classification)

    Day 3

    Morning

    1. More Advanced Topics
      • Hyperparameter Tuning and Regularization
      • Clustering & Dimensionality Reduction (K - Means, PCA, etc.)
      • Explainable AI: basic methods for interpretability
    2. Introduction to Deep Learning & Generative AI
      • Neural network basics
      • Brief overview of generative models

    Afternoon

    1. Scaling AI with No-Code AI Platforms
      • Benefits and limitations of no - low - code ML solutions
      • Demo or walkthrough of a no - code AI platform
    2. Case Studies & Optional Extended Project
      • Production pump anomaly detection/ROP Prediction
      • End to end AI workflow for drilling/geological insights

    Instructor : Mehdi Paydayesh

     

    CONFIRMED CLASS
    Aberdeen, Scotland, United Kingdom
    September 08-10, 2025
    $3,300
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    E&P Introduction and Fundamentals

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