Program Overview:

Energy professionals – current and future – have to gain deeper insights into operational data for making tougher decisions. UH Energy's new Upstream Energy Data Analytics Program answers this need for the upstream oil and gas industry.

Designed and presented by leaders from industry and accomplished faculty from the University of Houston System, the program provides a structured series of micro-credentials or “badges” that will provide the necessary data sciences skillset to facilitate developing solutions to current and emerging challenges using advanced data-based decision making.

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. Each badge is a 15-hours module, delivered over a 3-week period, and the badges are stackable. We are currently offering Silver Badge 4 (Introduction to Python) and Silver Badge 5 (Python Data Analysis). These programs will be delivered online - see Schedule for dates and times.

Schedule:

Instruction for each badge consists of 6, 2.5-hours online sessions. Each student should allow for 1.5 hrs. each for midterm and final test. Sessions are delivered two times per week, Monday and Wednesday, 6:00 pm - 8:30 pm, US Central Time. The dates for the two Silver Badges currently offered are:

Badge 4: Introduction to Python – August 22, 24, 29, 31 & September *05 & 07

* In observance of Labor Day, September 5th is a pre-recorded session.

Badge 5: Python Data Analysis - September 12, 14, 19, 21, 26 & 28

Pricing:​

Individual Badges (4 or 5): $900.00 per badge

Package (Badges 4 & 5): $1700.00

Prerequisites:

Either:

•        Rising senior in a bachelor’s degree program in engineering, technology or business with an understanding of upstream oil and gas operation such as seismic, drilling and production.

•        Upstream Oil and Gas Industry Professional.

Badge Descriptions:

•        Badge 4 - 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 and regular expressions. Upon completion of this course, participants should be able to understand existing scientific python codes as well as write their own python applications.

•        Badge 5 – Python Data Analysis: Badge 5 will focus on Python Data Analysis covering packages such as NumPy, Pandas and concepts of Data Wrangling, Plotting and Visualization and Data Aggregation. Modeling libraries such as Patsy, statsmodels and scikit-learn will also be introduced. 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.