Introduction to Energy Data Science in Python

INSTRUCTOR: John T. Foster, PhD
DISCIPLINE: Geoscience, Engineering, Unconventional Reservoirs, Multi-Disciplinary & Introductory
COURSE LENGTH (DAYS): 3 Days (Classroom) / 5 Half-Day Sessions (Live Online)
CEUS: 2.0 - 2.4
AVAILABILITY: Public & In-House

 

ATTEND AN UPCOMING CLASS:
Check back in periodically for updated Public course dates! To schedule an In-House course, contact SCA's Training Department at training@scacompanies.com.
 
WHO SHOULD ATTEND: Technical energy industry professionals (petroleum engineers, geoscientists) with basic Python proficiency.

COURSE DESCRIPTION: This three-day workshop focuses on the application of programming, visualizations, and data science solutions to energy industry data. Dr. Foster believes that Python will be a key tool in the future of data analytics and data science (it already is) and, as such, this workshop will be geared towards teaching students how to leverage the Python data science ecosystem (think Numpy, Pandas, Matplotlib, and Jupyter, etc). This course is designed to be highly interactive. You will be coding Python classes and functions, dashboards, and effective visualizations, using all free open-source tools. By the end of our workshop, you will have practical experience designing tools that will optimize workflows, as well as a firm understanding of how the Python data science ecosystem can be applied to energy industry data. As a deliverable, you will have created a dynamic dashboard using the knowledge and expertise in new tools gained over the course. Major course concepts will be covered in one-hour bundles, with 15 minutes of lecture, 15 minutes of live demonstration and 30 minutes of interactive coding, coaching, and troubleshooting.

LEARNING OUTCOMES:

  • Course Goal: build an Autotype User Interface (e.g. Dashboard) using open source tools and oil and gas data
  • Python 3 and Select Python Packages
    • Numpy / SciPy / Pandas / Matplotlib / Bokeh / Scikit-Learn / PyViz
  • Basics of Energy Machine Learning
  • Jupyter Project
  • Git / GitHub
  • Virtual Environments

 

COURSE CONTENT:

 

SAMPLE TOPIC(S) FROM THE CLASS:
“Energy Data Science in Python: Introduction to Pandas"

 

 

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