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Analytics and Machine Learning Applications in Oil Industry

Master essential skills in Python, SQL, data analytics, machine learning, and MLOps. Gain hands-on experience and practical knowledge to effectively apply advanced data science techniques in the oil industry.

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By Osama Abdelaziem
150.00
750.00

The Course Instructor

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Osama Abdelaziem
Petroleum Engineer
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  • Students : 22
  • Courses : 1

Osama is a production technology engineer with 5+ years of experience and a keen interest in digital oilfields. He holds a master’s degree in machine learning applications within petroleum engineering and has authored three papers on the same topic.

What you'll learn

Day#1: Python & SQL Basics
• Data Structure.
• Functions and Classes.
• Object Oriented Programming.
• Scripting.
• Common Python Libraries.
• SQL Expressions.
• Accessing databases with Python.

2.Day#2: Data Analytics in Python:
• Exploratory Data Analysis.
• Inferential Statistical Analysis.
• Visualization and Data Representation.
• Text Mining.


3.Day#3: Machine Learning with Python:
• Introduction to ML Applications in Petroleum Engineering.
• Supervised ML.
• Unsupervised ML.

4.Day#4: Deep Learning:
• Neural Networks.
• Computer Vision Applications.
• Large Language Models in Petroleum Engineering.


5. Day#5: MLOps:
• Experiment tracking.
• Orchestration.
• Deployment with Docker and Cloud.
• Monitoring.

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