No Code Analytics and Machine Learning in Energy
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Pricing
Individual Badge Price: $400 | Belt Bundles: $1,000
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Schedule
Dates: Data Processing: June 5 | Alt Machine Learning Ends: August 16
MON & WED | 6:00pm - 8:30pm
Executive Summary
Energy professionals – current and future – need deeper insights into operational data to make tougher decisions. UH Energy and the Subsea Systems Institute are delighted to present No Code Analytics and Machine Learning in Energy to address this need for the energy 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 three badges together form the Bronze Belt in No Code Analytics and Machine Learning in Energy.
PROGRAM OVERVIEW
The energy 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 energy industry. Many energy companies are already finding ways to implement data sciences solutions and are realizing tangible benefits, including enhanced sustainability and 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 shortage energy industry professionals with a practical knowledge of data sciences.
For this reason, UH Energy and the Subsea Systems Institute have developed the No Code Analytics and Machine Learning in Energy. This program is designed to equip current and aspiring professionals in the energy industry with data analytics concepts and hands on experience on applications with real world examples, using readily accessible tools that do not require extensive programming skills.
This program is designed, developed and delivered jointly by subject matter experts from the University of Houston System and from industry.
Who should attend?
No Code Analytics and Machine Learning in Energy has been designed with two distinct groups in mind:
- Those of you who are already in the energy industry and facing challenges daily in making operations more efficient while continuing to grow the energy business sustainably. No Code Analytics and Machine Learning in Energy will enhance your capabilities to get deeper insights from the data that you deal with, facilitating finding solutions to these challenges.
- If you are readying yourself for an energy career, you need to prepare yourself for a dynamic, exciting and challenging professional life. The No Code Analytics and Machine Learning in Energy program provides a unique perspective and a ready to apply practical skillset, giving you a competitively advantaged competence as you enter the energy marketplace.
Pricing
INDIVIDUAL BADGE PRICE:
$400
EACHBRONZE OR SILVER BELT BUNDLE (All 3 Badges purchased together):
$1,000
Credentialing Overview
The course is offered in 15-hour modules, each over a 3-week period. Digital badges are awarded for each module. Upon completing the initial 3 Badges, learners will earn the Bronze Belt in No Code Analytics and Machine Learning in Energy.
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.
Bronze Belt
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 energy industry datasets.
Silver Belt
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.
Gold Belt
The Gold Belt will introduce participants to tools and techniques for building and interpreting valid models for time series data using examples in the energy 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.
Instructors
Professor of Computer Science, University of Houston – Downtown
Associate Research Scientist, Department of Energy and Petroleum Engineering, University of Wyoming. Previously 27 years with Schlumberger, in a variety of technical, managerial and training positions.
Learning Objectives
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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
Either:
- Rising senior in a bachelor’s degree program in engineering, technology or business with an understanding of energy industry operations such as seismic, drilling and production
- Industry Professional
Testimonials
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Baskar Velusamy, Architect | Developer
"Always good to refresh your AI/ML skills...this time specific to oil&gas..best course for AI/ML who is in energy industry!"
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Ellya Saudale, Senior Geoscientist | Geomodeller| Seismic Interpreter | Asset Evaluations | Data Analytics
"I am grateful for the assistance from great lecturers; so I am thanking for Dr. Shastri, Kalyan for the excellent lectures and course exercises."