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, 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.
Each badge is a 15-hour module, delivered over a 3-week period, and the badges are stackable. The first three badges, which together form the Bronze Belt in Upstream Energy Data Analytics, are available online from UH Energy.
The oil and gas industry is undergoing significant changes, including repositioning operations to be cost-competitive in a world of low 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 will deliver the program in collaboration with NExT, a Schlumberger Company, UH Departments of Earth & Atmospheric Sciences and Petroleum Engineering and the HPE Data Sciences Institute at UH.
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.
BADGE 4 (Introduction to Python): *$250 for Non-UH Students
*FREE for current UH students (registered for-credit Spring 2021)
INDIVIDUAL BADGES (5 or 6): $900 per badge
SILVER BELT BUNDLE (Badges 4, 5 & 6, purchased together):
Non-UH Students: $1,950
Current UH Students (registered for-credit Spring 2021): $1,700
Schedule: Silver Belt
UH Energy is currently offering the Silver Belt in Upstream Energy Data Analytics. The Silver Belt consists of three badges. Instruction for each badge consists of 6, 2.5-hour 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 Thursday, from 5:30pm-8:00 pm, US Central Time.
Dates for the three badges are:
*The later badges build on the content of earlier badges, so participants are required to take the badges in the specified sequence.
The course is offered in 15 hour modules, each over a 3 week period. Digital badges are awarded for each module. For completing each group of 3 Badges, learners will earn a Belt. There are three belts in the program. The Introductory Belt (Bronze) is followed by an Intermediate Belt (Silver) and finally by an Advanced (Gold) Belt. The Belts and Badges will be a permanent addition to your skillset and resume.
The Bronze Belt provides the participants the tools and techniques to build and evaluate data-driven models via the machine learning approach. It covers the data analytics techniques to extract knowledge from raw data by building data-driven models. All aspects of data-mining – data exploration, data preprocessing, machine learning modeling, and model evaluation – are covered. The sessions combine theoretical knowledge with hands-on training of the data analytics techniques using real oil and gas datasets.
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.
The Gold Belt will introduce participants to tools and techniques for building and interpreting valid models for time series data using examples in the upstream oil and gas industry. Participants will also be introduced to fundamentals of Deep Learning, as well as Convolutional Neural Networks and Recurrent Neural Networks. Hands on sessions will focus on building CNN and RNN using the Keras library in Python.
After successfully completing the Introductory (Bronze) Belt, participants will understand how to extract knowledge from raw data and be skilled at:
- Data Exploration
- Data Preprocessing
- Machine Learning Modeling
- Evaluating Model Performance
- Improving Model Performance
Credentialing Program Prerequisites
- Rising senior in a bachelor’s degree program in engineering, technology or business with an understanding of upstream oil and gas operations such as seismic, drilling and production
- Industry Professional
Frequently Asked Questions
UH Energy will review your application to ensure that you satisfy the minimum requirements to register. For Badge 1, this means that you should either be:
- An Industry Professional - Priority is given to applicants from within the energy sector, with experience in upstream oil and gas operations
- A Student - Either in a graduate program, or a rising senior in a bachelor’s degree program in engineering, technology or business with an understanding of upstream oil and gas operations such as seismic, drilling and production
Micro-credentials are certifications for mastery of specific topic areas or skillsets. To earn a micro-credential, you typically have to complete a certain number of activities, assessments, or projects related to the topic.
Digital badges (or ebadges) are a validated indicator of accomplishment, skill, quality or interest that can be earned in various learning environments. Digital badges are now commonly used as “digital transcripts,” and they can be incorporated in LinkedIn profiles. Many badge earners also display their badges through social media.
Use and Acceptance: Micro-credentials and digital badges are now widely accepted by employers as evidence of competency in specific skills. They have been in use for roughly ten years, notably in the IT arena, where IBM has been a leader. IBM needed to train personnel to support rapidly changing product needs. Rather than using extended training programs, they developed training for minimum skillsets, and deployed this through online media. They awarded micro-credentials to successful candidates and issued digital badges to certify the awards. Many other companies, large and small, are now using digital credentials, as are many academic institutions, including the University of Houston, Harvard, Cambridge, and a large number of other universities.
Students who have registered can withdraw from the course at any time. However, participants need to withdraw two days before start of classes to receive a refund. If you have paid for the Bronze bundle (all three badges) and would like to withdraw after completing a badge, you may do so two days before the start of classes for the next badge to receive a refund for the remaining badges.