Module 1

Introduction to Data Science and Related Methodologies

A gentle introduction to Python Programming Language

Introduction to Python Environment and Ecosystem

Data Types and Structures in Python

Introduction to Data Visualization

Working with Tabulated Data using Pandas

Basics of Data Cleaning and Transformation using Pandas.

Creating Calculations and Data Exports.

Linking Excel, CSV, and TXT to Python

Module 2

Introduction to the Concept of Clustering

Understanding Distance Metrics

Introduction to the Scikit-Learn Library for Machine Learning

Fundamental Python Expressions and Functions

Introduction to Python Plotting

Anomaly Detection Techniques

Module 3

Introduction to the Concept of Clustering

Understanding Distance Metrics

Introduction to the Scikit-Learn Library for Machine Learning

Fundamental Python Expressions and Functions

Introduction to Python Plotting

Anomaly Detection Techniques

Module 4

Introduction to Continuous Data and Corresponding Relationships

Relationship Visualization and Correlation Matrix

Introduction to Regression Analysis

Linear Regression Fundamentals

Support Vector Regression (SVR)

Xtreme Gradient Regression (XGBoost Library)

Module 5

Introduction to Time-Bounded Data in the Oil and Gas Industry

Understanding Typical Decline Curve Analysis (DCA) and Its Limitations

Introduction to Time Series Analysis (TSA)

Time Series Data Patterns and Components

Comparing Decline Curve Analysis (DCA) to Time Series Analysis

Short-Term Production Prediction Using Time Series Analysis

Simple Moving Average (SMA) and Exponential Moving Average (EMA)

Introduction to AutoRegressive (AR) Models

On successful completion of this training course, PEA Certificate will be awarded to the delegates