Python Applications in Data Science, Artificial Intelligence, and Oil & Gas Data Analysis

Course Information:

• Duration: 7 lectures (total of 20 hours)

• Price: 100,000 IQD

• Course Type: Online via Zoom

• Start Date: September 19, 2024 (Thursday)

• Lecture Time: 8:00 PM

• Instructor: Mr. Nashaat Juma

• Certificate: Official, with QR code verification

• Requirements: A computer with Windows (X64) operating system

Topics Covered in the Course:

1. Introduction to Standard Python Programming

2. Introduction to the Comprehensive Python Ecosystem

3. Introduction to Data Science and the fundamentals of working with data

4. Methods for handling data (exploration, data processing, importing, and exporting data)

5. Data structuring and techniques to handle various data types (digital and non-digital, connected and fragmented)

6. Introduction to Oil & Gas data, its structure, and how to read and use it

7. Introduction to Excel data tables, linking them with Python, and ensuring data security and engineering

8. Introduction to visualizing and generating high-quality interactive charts, comparing conventional visualizations with advanced techniques

9. Introduction to event detection, relationships in network diagrams, elements, and their connections

10. Statistical techniques for data analysis and results visualization using Python

11. Diagnosing water production issues in oil wells using Python

12. Programming for interactive graphics using Python in software development

13. Introduction to analyzing and securing petro-physical values in well log files (LAS files)

14. Introduction to automated monitoring techniques using Python and AI, including machine learning

15. Introduction to AI techniques and machine learning

16. Introduction to clustering and operational data segmentation

17. Introduction to outlier detection (Outlier Factor) and its application in well data

18. Introduction to classifying equipment status and failure rates in wells using Python

19. Introduction to sequence analysis and its application to production data and equipment health.

For more information or to register:

• Phone: 0781 053 6592