Upstream Energy Data Analytics Program
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Application
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Pricing
Individual Badge Price: $900 each | Badge 4 & 5 Package: $1,700
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Schedule
Dates: Introduction to Python: August 22 | September 12
MON & WED | 6:00pm - 8:30pm
Executive Summary
Data sciences are already playing an important role in addressing several industry challenges. Industry leaders have validated these claims and have recognized that there is a workforce shortage in skilled data sciences with an understanding of the energy industry.
For this reason UH Energy, at the University of Houston, has developed the Upstream Energy Data Analytics Program, to equip current and aspiring professionals in the upstream oil and gas industry on data analytics concepts and hands on experience on applications with real world examples.
UH Energy delivers the program in collaboration with UH Departments of Earth & Atmospheric Sciences and Petroleum Engineering, and the HPE Data Sciences Institute at UH, and with subject matter experts from industry.
PROGRAM OVERVIEW
The oil and gas industry is undergoing significant changes, including repositioning operations to be cost-competitive in a world of rapidly changing oil prices, and meeting the growing demands of energy in a sustainable way.
This requires working in smarter and more efficient ways. Innovation has always been at the core of the oil and gas industry. Many oil and gas companies are already finding ways to implement data sciences solutions and are realizing tangible benefits, including competitive advantage.
Why This Program?
Data sciences are already playing an important role in addressing several industry challenges. Industry leaders have validated these claims and have recognized that there is a workforce shortage in skilled data sciences with an understanding of the energy industry.
For this reason UH Energy, at the University of Houston, has developed the Upstream Energy Data Analytics Program, to equip current and aspiring professionals in the upstream oil and gas industry on data analytics concepts and hands on experience on applications with real world examples.
UH Energy delivers the program in collaboration with UH Departments of Earth & Atmospheric Sciences and Petroleum Engineering, and the HPE Data Sciences Institute at UH, and with subject matter experts from industry.
Who should attend?
The Upstream Energy Data Analytics Program has been designed with two distinct groups in mind:
- Those of you who are already in the upstream industry and facing challenges daily in making operations more efficient while continuing to grow the business. The Upstream Energy Data Analytics program will enhance your capabilities to get deeper insights from the data that you deal with, facilitating finding solutions to above challenges.
- If you are readying yourself for an upstream career, you need to prepare yourself for a dynamic, exciting and challenging professional life. The Upstream Energy Data Analytics program provides a unique perspective and a ready to apply practical skillset, giving you a competitively advantaged competence as you enter the upstream oil and gas marketplace.
Learning Objectives
After successfully completing the Introduction to Python and Python Data Analysis badges, participants will understand and be skilled at:
- Python Programming
- Data Import/Export
- Data Types
- Control Statements
- Functions
- Reusable Data Analysis Models
- Writing programs to facilitate discoveries from Data
- Basic data processing
- Data Visualization
Pricing
INDIVIDUAL BADGE PRICE:
900
EACHBADGE 4 & 5 PACKAGE:
1,700
Credentialing Overview
The course is offered in 15-hour modules, each over a 3-week period. Digital badges are awarded for each module. Badges will be a permanent addition to your skillset and resume.
Introduction to Python
Python is an easy to learn, powerful programming language. It has efficient high-level data structures that make it suitable for rapid application development. Topics covered in this session will include:
- Data types
- Conditional & loop statements
- Functions
- Input/output
- Modules
- Regular expressions
Python Data Analysis
Participants will learn how to train and evaluate machine learning models using Python and Jupyter Notebook as the Integrated Development Environment. Hands-on sessions will be based on public upstream oil and gas datasets. Topics covered in this session include using:
- NumPy
- Pandas
- Concepts of Data Wrangling
- Plotting and Visualization
- Data Aggregation
- Modeling libraries
- Patsy
- Statsmodels
- Scikit-learn
Instructors
Dr. Mark Darby
Independent Consultant
Dr. Michael Nikolaou
Professor, Chemical and Biomolecular Engineering, University of Houston
Dr. Guan Qin
Associate Professor and Gulf Coast Section of the Society of Petroleum Engineers Endowed College Professor in Petroleum Engineering, Cullen College of Engineering, University of Houston
Dr. Suryanarayanan Radhakrishnan
Clinical Assistant Professor in Decision and Information Sciences, Bauer College of Business, University of Houston
Dr. Dvijesh Shastri
Associate Professor of Computer Science, University of Houston
Dr. Robert Stewart
Director, Allied Geophysical Labs, Hugh Roy and Lillie Cranz Cullen Distinguished University Chair in Exploration Geophysics, Professor of Geophysics, University of Houston
Dr. Kalyan Venugopal
Associate Research Scientist, Department of Energy and Petroleum Engineering, University of Wyoming
Credentialing Program Prerequisites
- Basic knowledge in computer devices.
- Background in machine learning is encouraged but not required.
Accelerating Credentials of Purpose and Value (ACPV)
Did you know?
UH Energy is working with UH’s Department of Petroleum Engineering, UH’s Department of Earth and Atmospheric Sciences, UH Clear Lake and UH Downtown to accelerate the integration of the Upstream Energy Data Analytics Program with the formal degree offerings at each of these institutions. To learn more about this please visit Accelerating Credentials of Purpose and Value