Name: ITIL 4 Specialist: Create, Deliver and Support: In-House Training
Price: 2295 GBP
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Loughborough

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			<p>This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.</p>
			<div><i></i> 5 Days 1 Exam</div>
			<div><i></i>  £595.00 incl. VAT</div>
			
			
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			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
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			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
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		<h3>Description</h3>
		<p></p><h3>Overview:</h3>
<p>Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organisations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organisations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.</p>
<h3>Course Objectives:</h3>
<p>In this course, you will implement AI techniques in order to solve business problems. You will:</p>
<p>• Specify a general approach to solve a given business problem that uses applied AI and ML.<br />• Collect and refine a dataset to prepare it for training and testing. <br />• Train and tune a machine learning model. <br />• Finalize a machine learning model and present the results to the appropriate audience. <br />• Build linear regression models. <br />• Build classification models. <br />• Build clustering models. <br />• Build decision trees and random forests. <br />• Build support-vector machines (SVMs). <br />• Build artificial neural networks (ANNs). <br />• Promote data privacy and ethical practices within AI and ML projects. </p>
<p> </p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4><span>Lesson 1: Solving Business Problems Using AI and ML</span></h4>
<p>Topic A: Identify AI and ML Solutions for Business Problems<br />Topic B: Formulate a Machine Learning Problem<br />Topic C: Select Appropriate Tools  </p>
<h4>Lesson 2: Collecting and Refining the Dataset</h4>
<p>Topic A: Collect the Dataset<br />Topic B: Analyze the Dataset to Gain Insights<br />Topic C: Use Visualizations to Analyze Data<br />Topic D: Prepare Data</p>
<h4>Lesson 3: Setting Up and Training a Model</h4>
<p>Topic A: Set Up a Machine Learning Model<br />Topic B: Train the Model </p>
<h4>Lesson 4: Finalizing a Model </h4>
<p>Topic A: Translate Results into Business Actions<br />Topic B: Incorporate a Model into a Long-Term Business Solution </p>
<h4>Lesson 5: Building Linear Regression Models</h4>
<p>Topic A: Build a Regression Model Using Linear Algebra<br />Topic B: Build a Regularized Regression Model Using Linear Algebra<br />Topic C: Build an Iterative Linear Regression Model </p>
<h4>Lesson 6: Building Classification Models</h4>
<p>Topic A: Train Binary Classification Models<br />Topic B: Train Multi-Class Classification Models<br />Topic C: Evaluate Classification Models<br />Topic D: Tune Classification Models</p>
<h4>Lesson 7: Building Clustering Models</h4>
<p>Topic A: Build k-Means Clustering Models<br />Topic B:  Build  Hierarchical  Clustering  Mode</p>
<h4>Lesson 8: Building Advanced Models</h4>
<p>Topic A: Build  Decision Tree Models<br />Topic B: Build Random Forest Model Lesson</p>
<h4>Lesson  9: Building Supports Vector Machines</h4>
<p>Topic A: Build SVM Models for Classification<br />Topic B:  Build SVM Models for Regression</p>
<h4>Lesson 10: Building Artificial Neural Networks</h4>
<p>Topic A: Build Multilayer Perceptrons (MLP)<br />Topic B: Build Convolutional Neural Networks (CNN)</p>
<h4>Lesson 11: Promoting Data Privacy and Ethical Practices</h4>
<p>Topic A: Protect Data Privacy<br />Topic B: Promote Ethical  Practices<br />Topic C: Establish Data Privacy and Ethics Policies</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing.</p>
<p>You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++.</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>The skills covered in this course converge on three areas-software development, applied math and statistics, and business analysis. Target students for this course may be strong in one or two or these of these areas and looking to round out their skills in the other areas so they can apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.  So the target student may be a programmer looking to develop additional skills to apply machine learning algorithms to business problems, or a data analyst who already has strong skills in applying math and statistics to business problems, but is looking to develop technology skills related to machine learning.   A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. </p>
<p>This course is also designed to assist students in preparing for the Certified Artificial Intelligence (AI) Practitioner certification.</p>
<p></p>

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
5 Days 1 Exam £595.00 incl. VAT
Want to run this event in-house? Enquire about running this event in-house 
Interested in attending? Have a suggestion about running this event near you?
Register your interest now
Description

Overview:
Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organisations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organisations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
Course Objectives:
In this course, you will implement AI techniques in order to solve business problems. You will:
• Specify a general approach to solve a given business problem that uses applied AI and ML.
• Collect and refine a dataset to prepare it for training and testing. 
• Train and tune a machine learning model. 
• Finalize a machine learning model and present the results to the appropriate audience. 
• Build linear regression models. 
• Build classification models. 
• Build clustering models. 
• Build decision trees and random forests. 
• Build support-vector machines (SVMs). 
• Build artificial neural networks (ANNs). 
• Promote data privacy and ethical practices within AI and ML projects. 
 

Modules/Lessons

Lesson 1: Solving Business Problems Using AI and ML
Topic A: Identify AI and ML Solutions for Business Problems
Topic B: Formulate a Machine Learning Problem
Topic C: Select Appropriate Tools 
Lesson 2: Collecting and Refining the Dataset
Topic A: Collect the Dataset
Topic B: Analyze the Dataset to Gain Insights
Topic C: Use Visualizations to Analyze Data
Topic D: Prepare Data
Lesson 3: Setting Up and Training a Model
Topic A: Set Up a Machine Learning Model
Topic B: Train the Model 
Lesson 4: Finalizing a Model
Topic A: Translate Results into Business Actions
Topic B: Incorporate a Model into a Long-Term Business Solution 
Lesson 5: Building Linear Regression Models
Topic A: Build a Regression Model Using Linear Algebra
Topic B: Build a Regularized Regression Model Using Linear Algebra
Topic C: Build an Iterative Linear Regression Model 
Lesson 6: Building Classification Models
Topic A: Train Binary Classification Models
Topic B: Train Multi-Class Classification Models
Topic C: Evaluate Classification Models
Topic D: Tune Classification Models
Lesson 7: Building Clustering Models
Topic A: Build k-Means Clustering Models
Topic B: Build Hierarchical Clustering Mode
Lesson 8: Building Advanced Models
Topic A: Build Decision Tree Models
Topic B: Build Random Forest Model Lesson
Lesson 9: Building Supports Vector Machines
Topic A: Build SVM Models for Classification
Topic B: Build SVM Models for Regression
Lesson 10: Building Artificial Neural Networks
Topic A: Build Multilayer Perceptrons (MLP)
Topic B: Build Convolutional Neural Networks (CNN)
Lesson 11: Promoting Data Privacy and Ethical Practices
Topic A: Protect Data Privacy
Topic B: Promote Ethical Practices
Topic C: Establish Data Privacy and Ethics Policies

Prerequisites

To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing.
You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++.

Target Student

The skills covered in this course converge on three areas-software development, applied math and statistics, and business analysis. Target students for this course may be strong in one or two or these of these areas and looking to round out their skills in the other areas so they can apply artificial intelligence (AI) systems, particularly machine learning models, to business problems. So the target student may be a programmer looking to develop additional skills to apply machine learning algorithms to business problems, or a data analyst who already has strong skills in applying math and statistics to business problems, but is looking to develop technology skills related to machine learning. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. 
This course is also designed to assist students in preparing for the Certified Artificial Intelligence (AI) Practitioner certification.


Mpi Learning - Professional Learning And Development Provider

Machine Learning (ML)

NLP Practitioner

Trainers Course

Azure Machine Learning

Microsoft AI-900

AI (Artificial Intelligence)

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

Certified Artificial Intelligence Practitioner

General Admission

Kuala Lumpur

<section style="color: rgb(33, 37, 41); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(33, 37, 41);"><h2 style="color: rgb(62, 57, 52); box-sizing: border-box;" fr-original-style=" color: rgb(62, 57, 52);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">About this Classroom Training</strong></h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">In the upcoming digital era, Python stands out as the language of the future for effective AI and data analytics implementation, particularly in the Oil and Gas sector. Its widespread adoption is attributed to extensive libraries, versatility, and a thriving community of developers consistently pushing the boundaries of the field. This training course will tailor a transformative learning experience for professionals in oil and gas.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Commencing with overview in the computer programming, participants delve into programming fundamentals and set up their Python coding environment. Participants will be able to explore flow control tools and functions, unlocking the full potential of Python. Furthermore, participants will gain expertise in various programming paradigms, with a particular focus on Object-Oriented Programming (OOP), a crucial foundation for building sophisticated applications.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Participants will navigate through file handling, internal modules, and external libraries like NumPy, Pandas, and Matplotlib, providing proficiency in data manipulation and visualization tailored for the challenges of real-life projects. Through a hands-on Data Analytics Project, participants will apply their skills to a real-world dataset, derive insights, and present findings.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This comprehensive workshop equips professionals with the tools for effective automation and data analytics in the Oil and Gas sector. Participants will experience a robust understanding of Python&rsquo;s applications, ready to drive impactful and data-driven initiatives in their professional journey.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This course will be delivered face-to-face over 5-day sessions, comprising of 8 hours per day, 1 hour lunch and 2 breaks of 15 minutes per day. Course Duration: 8 hours in total, 40 CPD points. Maximum number of participants: 30</p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Download your brochure</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Please Send me the Brochure for Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Email me the brochure</a></p></section><section style="color: rgb(33, 37, 41); box-sizing: border-box;" fr-original-style=" color: rgb(33, 37, 41);"><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseOne" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINING OBJECTIVES</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Acquire a comprehensive understanding of Python syntax, including variables, data types, and fundamental programming constructs.</li><li fr-original-style="" style="box-sizing: border-box;">Apply Python programming skills to analyze industry-specific datasets, extracting meaningful insights that can inform decision-making and operational efficiency.</li><li fr-original-style="" style="box-sizing: border-box;">Demonstrate the ability to automate routine tasks and streamline workflows within the Oil and Gas sector using Python.</li><li fr-original-style="" style="box-sizing: border-box;">Develop practical solutions and strategies using Python programming for challenges commonly faced in the industry, fostering hands-on experience and problem-solving capabilities.</li><li fr-original-style="" style="box-sizing: border-box;">Gain insights into emerging trends in digital technology within the industry and how Python can be leveraged for continuous adaptation and innovation.</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseTwo" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TARGET AUDIENCE</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">All Engineers and Technologists from diverse fields who are interested in utilizing Python programming and data analytics techniques to explore and address challenges within their respective domains.</li><li fr-original-style="" style="box-sizing: border-box;">Data Analysts and Scientists who working with data generated by sensors, monitoring equipment, and other sources within the industry.</li><li fr-original-style="" style="box-sizing: border-box;">IT and Automation Specialists who responsible for designing and implementing IT solutions and automation systems as well as who involve in developing and maintaining software application in the Oil and Gas sector.</li><li fr-original-style="" style="box-sizing: border-box;">Executives and Managers seeking a strategic understanding of how Python and data analytics can impact decision-making and operational efficiency in the industry.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals who interest in applying Python programming and data analytics techniques to study and solve challenges in the Oil and Gas field.</li><li fr-original-style="" style="box-sizing: border-box;">Individuals from related industries or backgrounds who are transitioning into roles within the Oil and Gas sector and wish to acquire relevant Python skills.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals from diverse backgrounds who recognize the growing importance of data analytics in the Oil and Gas sector and wish to enhance their skill set.</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapsecl" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">COURSE LEVEL</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Basic</li><li fr-original-style="" style="box-sizing: border-box;">Intermediate</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseThree" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINING METHODS</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The trainer will employ the &lsquo;learning by doing&rsquo; method by emphasizing practical application. Participants will be introduced to the concepts and theories using techniques that they can easily relate to. The learning experience is then reinforced by implementing the subject through real-life examples. The trainer will provide quizzes and tests for self-assessment and ensuring participants can measure their understanding and apply the knowledge effectively. This hands-on approach not only enhances comprehension but also empowers participants to confidently apply the learned skills in their professional endeavors.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Preparation ahead of the Class:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Participants are required to download the&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python 3.x</strong>&nbsp;version software onto their laptops.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The instructions are provided below:</p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Download&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Anaconda</strong>&nbsp;by visiting the Anaconda website (https://www.anaconda.com/products/distribution).</li><li fr-original-style="" style="box-sizing: border-box;">Click on the &ldquo;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Download</strong>&rdquo; button for the version that suits your operating system (Windows, macOS, Linux).</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Select the&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python 3.x</strong>&nbsp;version (e.g., Python 3.8) during the installation process.</li><li fr-original-style="" style="box-sizing: border-box;">Install Anaconda follow the instructions to run the installer. Install Just Me (Recommended).</li></ol></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseFive" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINER</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Your expert trainer is a seasoned multidisciplinary engineer with a 15-year professional journey, driven by an unwavering commitment to innovation and excellence. Armed with a Ph.D. in offshore engineering, he draws extensive insights from diverse industry sectors, notably oil and gas, where he served as a subsea pipeline engineer. His hands-on experience encompasses the entire spectrum, from design and manufacturing to installation and operations of offshore oil and gas facilities.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Previously at Rosen Group, your expert trainer developed digital tools for offshore structural assessments and risk-based inspection. He led research at the ARC Offshore Floating Facilities Hub on enhancing riser design and monitoring using Python and data analytics. He performed design verification for INPEX, Chevron, and Apache on subsea pipelines, risers, umbilicals, and LNG facilities, and was a deputy project manager on verifying the Ichthys gas pipeline. He conducted risk-based inspection and auditing of the Ichthys LNG plant for DNV GL. He also worked as a structural engineer at Advanced Building Engineers designing steel structures, buildings, and other components. Meanwhile, at the University of Western Australia (UWA), your expert trainer developed AI and data solutions for the oil &amp; gas industry focused on condition monitoring and probabilistic assessments and led research on offshore facilities by creating tools for analysis and machine learning.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">His academic pursuit culminated in a thesis that underscores his proficiency in employing data science and machine learning, primarily through Python. His research focused on optimising asset integrity management for offshore oil and gas assets, showcasing a seamless integration of engineering and cutting-edge technology. In 2023, he fully unleash AI-driven solutions across diverse sectors. Currently, he actively contributes to mineral resource exploration and assists oil and gas operators in the effective implementation of new AI and digital technologies.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">His dedication to knowledge dissemination is evident through his role as a global educator. Over the past five years, he has conducted Python programming lectures at universities and industries, reaching over 1000 novices. His unwavering commitment to lifelong learning, coupled with a growth mindset have positions him as a transformative trainer in the realms of applied AI, data science, and engineering in oil and gas sector</p><section style="color: rgb(33, 37, 41); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(33, 37, 41);"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Download your brochure</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Please Send me the Brochure for Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Email me the brochure</a></p></section></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseCS" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);">POST TRAINING COACHING SUPPORT (OPTIONAL)</a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">To further optimise your learning experience from our courses, we also offer individualized &ldquo;One to One&rdquo; coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br fr-original-style="" style="box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Request%20for%20further%20information%20regarding%20post%20training%20coaching%20support" target="_blank" style="color: rgb(0, 123, 255); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(0, 123, 255);">Request for further information post training support</a>&nbsp;and fees applicable.</p></div></section>

About this Classroom Training
In the upcoming digital era, Python stands out as the language of the future for effective AI and data analytics implementation, particularly in the Oil and Gas sector. Its widespread adoption is attributed to extensive libraries, versatility, and a thriving community of developers consistently pushing the boundaries of the field. This training course will tailor a transformative learning experience for professionals in oil and gas.
Commencing with overview in the computer programming, participants delve into programming fundamentals and set up their Python coding environment. Participants will be able to explore flow control tools and functions, unlocking the full potential of Python. Furthermore, participants will gain expertise in various programming paradigms, with a particular focus on Object-Oriented Programming (OOP), a crucial foundation for building sophisticated applications.
Participants will navigate through file handling, internal modules, and external libraries like NumPy, Pandas, and Matplotlib, providing proficiency in data manipulation and visualization tailored for the challenges of real-life projects. Through a hands-on Data Analytics Project, participants will apply their skills to a real-world dataset, derive insights, and present findings.
This comprehensive workshop equips professionals with the tools for effective automation and data analytics in the Oil and Gas sector. Participants will experience a robust understanding of Python’s applications, ready to drive impactful and data-driven initiatives in their professional journey.
This course will be delivered face-to-face over 5-day sessions, comprising of 8 hours per day, 1 hour lunch and 2 breaks of 15 minutes per day. Course Duration: 8 hours in total, 40 CPD points. Maximum number of participants: 30
Download your brochure
Email me the brochure
TRAINING OBJECTIVES
Acquire a comprehensive understanding of Python syntax, including variables, data types, and fundamental programming constructs.
Apply Python programming skills to analyze industry-specific datasets, extracting meaningful insights that can inform decision-making and operational efficiency.
Demonstrate the ability to automate routine tasks and streamline workflows within the Oil and Gas sector using Python.
Develop practical solutions and strategies using Python programming for challenges commonly faced in the industry, fostering hands-on experience and problem-solving capabilities.
Gain insights into emerging trends in digital technology within the industry and how Python can be leveraged for continuous adaptation and innovation.
TARGET AUDIENCE
All Engineers and Technologists from diverse fields who are interested in utilizing Python programming and data analytics techniques to explore and address challenges within their respective domains.
Data Analysts and Scientists who working with data generated by sensors, monitoring equipment, and other sources within the industry.
IT and Automation Specialists who responsible for designing and implementing IT solutions and automation systems as well as who involve in developing and maintaining software application in the Oil and Gas sector.
Executives and Managers seeking a strategic understanding of how Python and data analytics can impact decision-making and operational efficiency in the industry.
Professionals who interest in applying Python programming and data analytics techniques to study and solve challenges in the Oil and Gas field.
Individuals from related industries or backgrounds who are transitioning into roles within the Oil and Gas sector and wish to acquire relevant Python skills.
Professionals from diverse backgrounds who recognize the growing importance of data analytics in the Oil and Gas sector and wish to enhance their skill set.
COURSE LEVEL
Basic
Intermediate
TRAINING METHODS
The trainer will employ the ‘learning by doing’ method by emphasizing practical application. Participants will be introduced to the concepts and theories using techniques that they can easily relate to. The learning experience is then reinforced by implementing the subject through real-life examples. The trainer will provide quizzes and tests for self-assessment and ensuring participants can measure their understanding and apply the knowledge effectively. This hands-on approach not only enhances comprehension but also empowers participants to confidently apply the learned skills in their professional endeavors.
Preparation ahead of the Class:
Participants are required to download the Python 3.x version software onto their laptops.
The instructions are provided below:
Download Anaconda by visiting the Anaconda website (https://www.anaconda.com/products/distribution).
Click on the “Download” button for the version that suits your operating system (Windows, macOS, Linux).
Select the Python 3.x version (e.g., Python 3.8) during the installation process.
Install Anaconda follow the instructions to run the installer. Install Just Me (Recommended).
TRAINER
Your expert trainer is a seasoned multidisciplinary engineer with a 15-year professional journey, driven by an unwavering commitment to innovation and excellence. Armed with a Ph.D. in offshore engineering, he draws extensive insights from diverse industry sectors, notably oil and gas, where he served as a subsea pipeline engineer. His hands-on experience encompasses the entire spectrum, from design and manufacturing to installation and operations of offshore oil and gas facilities.
Previously at Rosen Group, your expert trainer developed digital tools for offshore structural assessments and risk-based inspection. He led research at the ARC Offshore Floating Facilities Hub on enhancing riser design and monitoring using Python and data analytics. He performed design verification for INPEX, Chevron, and Apache on subsea pipelines, risers, umbilicals, and LNG facilities, and was a deputy project manager on verifying the Ichthys gas pipeline. He conducted risk-based inspection and auditing of the Ichthys LNG plant for DNV GL. He also worked as a structural engineer at Advanced Building Engineers designing steel structures, buildings, and other components. Meanwhile, at the University of Western Australia (UWA), your expert trainer developed AI and data solutions for the oil & gas industry focused on condition monitoring and probabilistic assessments and led research on offshore facilities by creating tools for analysis and machine learning.
His academic pursuit culminated in a thesis that underscores his proficiency in employing data science and machine learning, primarily through Python. His research focused on optimising asset integrity management for offshore oil and gas assets, showcasing a seamless integration of engineering and cutting-edge technology. In 2023, he fully unleash AI-driven solutions across diverse sectors. Currently, he actively contributes to mineral resource exploration and assists oil and gas operators in the effective implementation of new AI and digital technologies.
His dedication to knowledge dissemination is evident through his role as a global educator. Over the past five years, he has conducted Python programming lectures at universities and industries, reaching over 1000 novices. His unwavering commitment to lifelong learning, coupled with a growth mindset have positions him as a transformative trainer in the realms of applied AI, data science, and engineering in oil and gas sector
Download your brochure
Email me the brochure
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized “One to One” coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.
Request for further information post training support and fees applicable.

EnergyEdge - Training for a Sustainable Energy Future

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

Assessment Based Training - Python Programming & Analytics for the Oil & Gas Sector - Maximising Value from Data Assets

Team of 10, pp

Normal Fee, pp

<div>
</div>
<section>
<div>
<h2>About this training course</h2>
<p>Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion.</p>
<p>Understanding of these important production concepts is a must have to exploit the existing assets profitably.</p>
<p><strong>Unique Features:</strong></p>
<ul>
<li>Hands-on usage of <strong>SNAP Software</strong> to solve gas-lift exercises</li>
<li>Discussion on <strong>digital oil field</strong></li>
<li><strong>Machine learning</strong> <strong>applications</strong> in gas-lift optimization</li>
</ul>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p>After the completion of this training course, participants will be able to:</p>
<ul>
<li>Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses</li>
<li>Easily recognize the different components from downhole to the surface and their basic structural and operational features</li>
<li>Design and analyze different components using appropriate software tools</li>
<li>Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation</li>
<li>Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization</li>
<li>Learn about use cases of Machine learning and artificial intelligence in the artificial lift</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p>This training course is suitable and will greatly benefit the following specific groups:</p>
<ul>
<li>Production, reservoir, completion, drilling and facilities engineers, analysts, and operators</li>
<li>Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course.</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Intermediate</li>
<li>Advanced</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Training Methods 

</div>
<div id="collapseThree">
<div>
<p><span>The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization.</span></p>
<p><em><span>Course Duration: 5 days in total (35 hours).</span></em></p>
<p><strong><span>Training Schedule</span></strong></p>
<p><span>0830 - Registration </span><span>0900 - Start of training </span><span>1030 - Morning Break </span><span>1045 - Training recommences </span><span>1230 - Lunch Break </span><span>1330 - Training recommences </span><span>1515 - Evening break </span><span>1530 - Training recommences </span><span>1700 - End of Training</span></p>
<p><span>The maximum number of participants allowed for this training course is 20.</span></p>
<p>This course is also available through our Virtual Instructor Led Training (VILT) format.</p>
<p><strong>Prerequisites:</strong></p>
<ul>
<li>Understanding of petroleum production concepts.</li>
<li>Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software.</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p>Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.</p>
<p><strong>Highlighted Work Experience: </strong></p>
<ul>
<li>At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.</li>
<li>Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.</li>
<li>Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.</li>
<li>Developed a workshop on digital oilfield approaches for production engineers.</li>
</ul>
<p><strong>Patents:</strong></p>
<ul>
<li>Principal inventor: 'Smarter Slug Flow Conditioning and Control'</li>
<li>Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'</li>
<li>Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'</li>
</ul>
<p><strong>Worldwide Experience in Training / Seminar / Workshop Deliveries:</strong></p>
<ul>
<li>Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&amp;T, Louisiana State, U of Southern California, and U of Houston.</li>
<li>He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:
<ul>
<li><u>Companies:</u> Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.</li>
<li><u>Countries:</u> USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.</li>
<li>Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this training course
Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion.
Understanding of these important production concepts is a must have to exploit the existing assets profitably.
Unique Features:
Hands-on usage of SNAP Software to solve gas-lift exercises
Discussion on digital oil field
Machine learning applications in gas-lift optimization
Training Objectives
After the completion of this training course, participants will be able to:
Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses
Easily recognize the different components from downhole to the surface and their basic structural and operational features
Design and analyze different components using appropriate software tools
Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation
Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization
Learn about use cases of Machine learning and artificial intelligence in the artificial lift
Target Audience
This training course is suitable and will greatly benefit the following specific groups:
Production, reservoir, completion, drilling and facilities engineers, analysts, and operators
Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course.
Course Level
Intermediate
Advanced
Training Methods
The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization.
Course Duration: 5 days in total (35 hours).
Training Schedule
0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training
The maximum number of participants allowed for this training course is 20.
This course is also available through our Virtual Instructor Led Training (VILT) format.
Prerequisites:
Understanding of petroleum production concepts.
Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software.
Trainer
Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.
Highlighted Work Experience: 
At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.
Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.
Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.
Developed a workshop on digital oilfield approaches for production engineers.
Patents:
Principal inventor: 'Smarter Slug Flow Conditioning and Control'
Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'
Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'
Worldwide Experience in Training / Seminar / Workshop Deliveries:
Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston.
He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:

Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.
Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.
Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information post training support and fees applicable
Accreditions And Affliations

Renewable Energy

Oil & Gas

Artificial Lift and Real-Time Production Optimization in Digital Oilfield

<div>
</div>
<section>
<div>
<h2><strong>About this Training Course</strong></h2>
<p>There are various kinds of geophysical data available. They are separated into seismic and non-seismic (multi-physics) data. Non-seismic or multi-physics data (which includes gravity, magnetics, electrical, electromagnetics, spectral etc - apart from providing complimentary information to seismic) is the main source of information for very shallow subsurface applications such as engineering, mapping pollution, archaeology, geothermal energy, and related areas. This 5 full-day blended course will focus specifically on seismic data which is the main method used in the Oil &amp; Gas industry.</p>
<p>In this blended course, participants will be equipped to understand that seismic data represents the movement of the surface, resulting from waves generated by a source, dynamite or vibrator which are reflected by changes in the subsurface rocks. The basic principles of acquisition and processing will be explained and insights into advanced methods, allowing a much more accurate interpretation of seismic data than previously considered possible, will also be provided.</p>
<p>This blended course contains an introduction to Machine Learning and its important role in all aspects of seismic acquisition, processing, and interpretation. There is no need to know in detail how the algorithms work internally but it is necessary to know how to use them correctly to achieve optimum results.</p>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p>By attending this course, participants will be able to acquire the following:</p>
<ul>
<li>Obtain an understanding of the strengths and limitations of geophysical methods, specifically seismic, and the costs and risks involved, and how to reduce these.</li>
<li>Be able to communicate more effectively with staff in other disciplines.</li>
<li>Understand the potential applications of seismic data and know how to formulate the requirements needed for prospect and field evaluation.</li>
<li>Gain an awareness of modern seismic technology.</li>
<li>Apply the learning in a series of practical, illustrative exercises.</li>
<li>Know what types of questions to ask to assess the necessary quality of a seismic project in its role in a sequence of E&amp;P activities</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p>The blended course is intended for <strong>non-geophysicists who have intensive interaction with geophysicists</strong>. But it may be of interest to those who want to know about the recent progress made in geophysics, leading to amazing imaging results, which could not be imagined a decade ago. The blended course will bring to the attention of the geologists, petrophysicists and reservoir/petroleum engineers an awareness of how the data they will work with is acquired and processed by the geophysicist. It will introduce the concepts that are of importance in geophysics and thus relevant for non-geophysicists to know and be able to communicate with geophysicists as well as formulate their requests.</p>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Intermediate</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p>Your expert course leader has degree in Geology (University of Leiden), a Master's degree in Theoretical Geophysics (University of Utrecht) and a PhD in Utrecht on 'Full wave theory and the structure of the lower mantle'. This involved forward modelling of P- and S-waves diffracted around the core-mantle boundary and comparison of the frequency-dependent attenuation of the signal with those obtained from major earthquakes observed at long offsets in the 'shadow zone' of the core. These observations were then translated into rock properties of the D' transition zone.</p>
<p>After his PhD, he joined Shell Research in The Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. He subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben. As part of the Quantitative Interpretation assignment, he was also actively involved in managing, processing and interpreting Offshore Seismic Profiling experiments.</p>
<p>After his return to The Netherlands, he headed a team for the development of 3D interpretation methods using multi-attribute statistical and pattern recognition analysis on workstations. After a period of Quality Assurance of 'Contractor' software for seismic processing, he became responsible for Geophysics in the Shell Learning Centre. During that period, he was also a part-time professor in Applied Geophysics at the University of Utrecht.</p>
<p>From 2001 to 2005, he worked on the development of Potential Field Methods (Gravity, Magnetics) for detecting oil and gas. Finally, he became a champion on the use of EM methods and became involved in designing acquisition, processing and interpretation methods for Marine Controlled Source EM (CSEM) methods.</p>
<p>After his retirement from Shell, he founded his own company, specialising in courses on acquisition, processing and interpretation of geophysical data (seismic, gravity, magnetic and electromagnetic data), providing courses to International and National energy companies.</p>
<p>In the last couple of years, he became keenly interested in the use of Machine Learning in Geophysics. Apart from incorporating 'Artificial Intelligence' in his courses, he also developed a dedicated Machine Learning course for geophysics.</p>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this Training Course
There are various kinds of geophysical data available. They are separated into seismic and non-seismic (multi-physics) data. Non-seismic or multi-physics data (which includes gravity, magnetics, electrical, electromagnetics, spectral etc - apart from providing complimentary information to seismic) is the main source of information for very shallow subsurface applications such as engineering, mapping pollution, archaeology, geothermal energy, and related areas. This 5 full-day blended course will focus specifically on seismic data which is the main method used in the Oil & Gas industry.
In this blended course, participants will be equipped to understand that seismic data represents the movement of the surface, resulting from waves generated by a source, dynamite or vibrator which are reflected by changes in the subsurface rocks. The basic principles of acquisition and processing will be explained and insights into advanced methods, allowing a much more accurate interpretation of seismic data than previously considered possible, will also be provided.
This blended course contains an introduction to Machine Learning and its important role in all aspects of seismic acquisition, processing, and interpretation. There is no need to know in detail how the algorithms work internally but it is necessary to know how to use them correctly to achieve optimum results.
Training Objectives
By attending this course, participants will be able to acquire the following:
Obtain an understanding of the strengths and limitations of geophysical methods, specifically seismic, and the costs and risks involved, and how to reduce these.
Be able to communicate more effectively with staff in other disciplines.
Understand the potential applications of seismic data and know how to formulate the requirements needed for prospect and field evaluation.
Gain an awareness of modern seismic technology.
Apply the learning in a series of practical, illustrative exercises.
Know what types of questions to ask to assess the necessary quality of a seismic project in its role in a sequence of E&P activities
Target Audience
The blended course is intended for non-geophysicists who have intensive interaction with geophysicists. But it may be of interest to those who want to know about the recent progress made in geophysics, leading to amazing imaging results, which could not be imagined a decade ago. The blended course will bring to the attention of the geologists, petrophysicists and reservoir/petroleum engineers an awareness of how the data they will work with is acquired and processed by the geophysicist. It will introduce the concepts that are of importance in geophysics and thus relevant for non-geophysicists to know and be able to communicate with geophysicists as well as formulate their requests.
Course Level
Intermediate
Trainer
Your expert course leader has degree in Geology (University of Leiden), a Master's degree in Theoretical Geophysics (University of Utrecht) and a PhD in Utrecht on 'Full wave theory and the structure of the lower mantle'. This involved forward modelling of P- and S-waves diffracted around the core-mantle boundary and comparison of the frequency-dependent attenuation of the signal with those obtained from major earthquakes observed at long offsets in the 'shadow zone' of the core. These observations were then translated into rock properties of the D' transition zone.
After his PhD, he joined Shell Research in The Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. He subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben. As part of the Quantitative Interpretation assignment, he was also actively involved in managing, processing and interpreting Offshore Seismic Profiling experiments.
After his return to The Netherlands, he headed a team for the development of 3D interpretation methods using multi-attribute statistical and pattern recognition analysis on workstations. After a period of Quality Assurance of 'Contractor' software for seismic processing, he became responsible for Geophysics in the Shell Learning Centre. During that period, he was also a part-time professor in Applied Geophysics at the University of Utrecht.
From 2001 to 2005, he worked on the development of Potential Field Methods (Gravity, Magnetics) for detecting oil and gas. Finally, he became a champion on the use of EM methods and became involved in designing acquisition, processing and interpretation methods for Marine Controlled Source EM (CSEM) methods.
After his retirement from Shell, he founded his own company, specialising in courses on acquisition, processing and interpretation of geophysical data (seismic, gravity, magnetic and electromagnetic data), providing courses to International and National energy companies.
In the last couple of years, he became keenly interested in the use of Machine Learning in Geophysics. Apart from incorporating 'Artificial Intelligence' in his courses, he also developed a dedicated Machine Learning course for geophysics.
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information post training support and fees applicable
Accreditions And Affliations

Fundamentals of Seismic for Non-Geophysicists

<div>
</div>
<section>
<div>
<h2>About this training course</h2>
<p>Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts.</p>
<p>This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion.</p>
<p><strong>Unique Features:</strong></p>
<ul>
<li>Hands-on usage of <strong>SNAP Software</strong> to solve gas-lift exercises</li>
<li>Discussion on <strong>digital oil field</strong></li>
<li><strong>Machine learning</strong> <strong>applications</strong> in gas-lift optimization</li>
</ul>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p>After the completion of this training course, participants will be able to:</p>
<ul>
<li>Understand the fundamental theories and procedures related to Gas-Lift operations</li>
<li>Easily recognize the different components of the gas-lift system and their basic structural and operational features</li>
<li>Be able to design a gas-lift installation</li>
<li>Comprehend how digital oilfield tools help address ESP challenges</li>
<li>Examine recent advances in real-time approaches to the production monitoring and lift management</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p>This training course is suitable and will greatly benefit the following specific groups:</p>
<ul>
<li>Production, reservoir, completion, drilling and facilities engineers, analysts, and operators</li>
<li>Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Intermediate</li>
<li>Advanced</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Training Methods 

</div>
<div id="collapseThree">
<div>
<p><span>The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization.</span></p>
<p><em><span>Course Duration: 5 days in total (35 hours).</span></em></p>
<p><strong><span>Training Schedule</span></strong></p>
<p><span>0830 - Registration </span><span>0900 - Start of training </span><span>1030 - Morning Break </span><span>1045 - Training recommences </span><span>1230 - Lunch Break </span><span>1330 - Training recommences </span><span>1515 - Evening break </span><span>1530 - Training recommences </span><span>1700 - End of Training</span></p>
<p><span>The maximum number of participants allowed for this training course is 20.</span></p>
<p>This course is also available through our Virtual Instructor Led Training (VILT) format.</p>
<p><strong>Prerequisites:</strong></p>
<ul>
<li>Understanding of petroleum production concepts.</li>
<li>Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software.</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p>Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.</p>
<p><strong>Highlighted Work Experience: </strong></p>
<ul>
<li>At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.</li>
<li>Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.</li>
<li>Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.</li>
<li>Developed a workshop on digital oilfield approaches for production engineers.</li>
</ul>
<p><strong>Patents:</strong></p>
<ul>
<li>Principal inventor: 'Smarter Slug Flow Conditioning and Control'</li>
<li>Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'</li>
<li>Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'</li>
</ul>
<p><strong>Worldwide Experience in Training / Seminar / Workshop Deliveries:</strong></p>
<ul>
<li>Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&amp;T, Louisiana State, U of Southern California, and U of Houston.</li>
<li>He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:
<ul>
<li><u>Companies:</u> Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.</li>
<li><u>Countries:</u> USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.</li>
<li>Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this training course
Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts.
This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion.
Unique Features:
Hands-on usage of SNAP Software to solve gas-lift exercises
Discussion on digital oil field
Machine learning applications in gas-lift optimization
Training Objectives
After the completion of this training course, participants will be able to:
Understand the fundamental theories and procedures related to Gas-Lift operations
Easily recognize the different components of the gas-lift system and their basic structural and operational features
Be able to design a gas-lift installation
Comprehend how digital oilfield tools help address ESP challenges
Examine recent advances in real-time approaches to the production monitoring and lift management
Target Audience
This training course is suitable and will greatly benefit the following specific groups:
Production, reservoir, completion, drilling and facilities engineers, analysts, and operators
Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs
Course Level
Intermediate
Advanced
Training Methods
The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization.
Course Duration: 5 days in total (35 hours).
Training Schedule
0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training
The maximum number of participants allowed for this training course is 20.
This course is also available through our Virtual Instructor Led Training (VILT) format.
Prerequisites:
Understanding of petroleum production concepts.
Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software.
Trainer
Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.
Highlighted Work Experience: 
At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.
Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.
Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.
Developed a workshop on digital oilfield approaches for production engineers.
Patents:
Principal inventor: 'Smarter Slug Flow Conditioning and Control'
Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'
Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'
Worldwide Experience in Training / Seminar / Workshop Deliveries:
Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston.
He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:

Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.
Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.
Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information post training support and fees applicable
Accreditions And Affliations

Gas Lift Design & Optimization using NODAL Analysis

<div>
</div>
<section>
<div>
<h2><strong>About this Course</strong></h2>
<p>This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data.</p>
<p>A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning.</p>
<p>With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties.</p>
<p>On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side.</p>
<p>This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting.</p>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p><span>This course offers a comprehensive approach to all aspects of load forecasting:</span></p>
<ul>
<li><span>Gain a perspective of load forecasting from both operators in the generating plant and system operators.</span></li>
<li><span>Understand and review the advanced load forecasting concepts and forecasting methodologies</span></li>
<li><span>Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames</span></li>
<li><span>Appreciate market segmentation and econometric framework for long term forecasts</span></li>
<li><span>Find out the most recent practical application of load forecasting as examples from large power companies</span></li>
<li><span>Get access to recent industry reports and developments</span></li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<ul>
<li><span>Energy load forecasting professionals from power plant and system operators</span></li>
<li><span>Energy planners and energy outlook forecasters and plant operators</span></li>
<li><span>Fuel procurement professionals</span></li>
<li><span>Planners and schedulers of thermal generating units</span></li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Intermediate</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p><span>Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.</span></p>
<p><span>With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.</span></p>
<p><span>Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are:</span></p>
<ul>
<li><span>Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020</span></li>
<li><span>Assessment of OETC Control Centre, Oman, December 2019</span></li>
<li><span>Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019</span></li>
<li><span>Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia)</span></li>
<li><span>The Modern Power System: Impact of the Power Electronics on the Power System</span></li>
<li><span>The Digital Utility, AI and Blockchain</span></li>
<li><span>Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada</span></li>
<li><span>Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia)</span></li>
<li><span>Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level.</span></li>
<li><span>Enterprise Risk methodology, EDP, Portugal</span></li>
<li><span>Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia</span></li>
<li><span>Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA)</span></li>
<li><span>EUSN, ENERGY &amp; UTILITIES SECTOR NETWORK, Government of Canada, 2016</span></li>
<li><span>Connected+, IOT, Toronto, Canada September 2016 and 2015</span></li>
<li><span>Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014</span></li>
<li><span>Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010</span></li>
</ul>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this Course
This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data.
A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning.
With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties.
On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side.
This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting.
Training Objectives
This course offers a comprehensive approach to all aspects of load forecasting:
Gain a perspective of load forecasting from both operators in the generating plant and system operators.
Understand and review the advanced load forecasting concepts and forecasting methodologies
Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames
Appreciate market segmentation and econometric framework for long term forecasts
Find out the most recent practical application of load forecasting as examples from large power companies
Get access to recent industry reports and developments
Target Audience
Energy load forecasting professionals from power plant and system operators
Energy planners and energy outlook forecasters and plant operators
Fuel procurement professionals
Planners and schedulers of thermal generating units
Course Level
Intermediate
Trainer
Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.
With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.
Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are:
Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020
Assessment of OETC Control Centre, Oman, December 2019
Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019
Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia)
The Modern Power System: Impact of the Power Electronics on the Power System
The Digital Utility, AI and Blockchain
Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada
Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia)
Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level.
Enterprise Risk methodology, EDP, Portugal
Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia
Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA)
EUSN, ENERGY & UTILITIES SECTOR NETWORK, Government of Canada, 2016
Connected+, IOT, Toronto, Canada September 2016 and 2015
Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014
Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information post training support and fees applicable
Accreditions And Affliations

Advanced Load Forecasting & Methodology

<div>
</div>
<section>
<div>
<h2>About this training course</h2>
<p><strong>Business Impact:</strong> The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets.</p>
<p>Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles.</p>
<p><strong>Unique Features:</strong></p>
<ul>
<li><strong><em>Eight business use cases</em></strong> covering their business impact, code walkthroughs for most all and solution approach.</li>
<li><strong><em>Industry data sets</em></strong> for participants to practice on and take home.</li>
<li>No software or complicated Python frameworks required.</li>
</ul>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p>After the completion of this training course, participants will be able to:</p>
<ul>
<li>Understand digital oil field transformation and its impact on business</li>
<li>Examine machine learning methods</li>
<li>Review workflows and code implementations</li>
<li>After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p>This training course is suitable and will greatly benefit the following specific groups:</p>
<ul>
<li>Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Intermediate</li>
<li>Advanced</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Training Methods 

</div>
<div id="collapseThree">
<div>
<p><span>The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution.</span></p>
<p><em><span>Course Duration: 2 days in total (14 hours).</span></em></p>
<p><strong><span>Training Schedule</span></strong></p>
<p><span>0830 - Registration </span><span>0900 - Start of training </span><span>1030 - Morning Break </span><span>1045 - Training recommences </span><span>1230 - Lunch Break </span><span>1330 - Training recommences </span><span>1515 - Evening break </span><span>1530 - Training recommences </span><span>1700 - End of Training</span></p>
<p><span>The maximum number of participants allowed for this training course is 20.</span></p>
<p>This course is also available through our Virtual Instructor Led Training (VILT) format.</p>
<p><strong>Prerequisites:</strong></p>
<ul>
<li>Understanding of petroleum production concepts</li>
<li>Knowledge of Python is not a must but preferred to get the full benefit.</li>
<li>The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises</li>
<li>Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free)</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p>Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.</p>
<p><strong>Highlighted Work Experience: </strong></p>
<ul>
<li>At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.</li>
<li>Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.</li>
<li>Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.</li>
<li>Developed a workshop on digital oilfield approaches for production engineers.</li>
</ul>
<p><strong>Patents:</strong></p>
<ul>
<li>Principal inventor: 'Smarter Slug Flow Conditioning and Control'</li>
<li>Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'</li>
<li>Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'</li>
</ul>
<p><strong>Worldwide Experience in Training / Seminar / Workshop Deliveries:</strong></p>
<ul>
<li>Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&amp;T, Louisiana State, U of Southern California, and U of Houston.</li>
<li>He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:
<ul>
<li><u>Companies:</u> Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.</li>
<li><u>Countries:</u> USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.</li>
<li>Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

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<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

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<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this training course
Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets.
Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles.
Unique Features:
Eight business use cases covering their business impact, code walkthroughs for most all and solution approach.
Industry data sets for participants to practice on and take home.
No software or complicated Python frameworks required.
Training Objectives
After the completion of this training course, participants will be able to:
Understand digital oil field transformation and its impact on business
Examine machine learning methods
Review workflows and code implementations
After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models
Target Audience
This training course is suitable and will greatly benefit the following specific groups:
Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets
Course Level
Intermediate
Advanced
Training Methods
The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution.
Course Duration: 2 days in total (14 hours).
Training Schedule
0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training
The maximum number of participants allowed for this training course is 20.
This course is also available through our Virtual Instructor Led Training (VILT) format.
Prerequisites:
Understanding of petroleum production concepts
Knowledge of Python is not a must but preferred to get the full benefit.
The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises
Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free)
Trainer
Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.
Highlighted Work Experience: 
At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.
Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.
Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.
Developed a workshop on digital oilfield approaches for production engineers.
Patents:
Principal inventor: 'Smarter Slug Flow Conditioning and Control'
Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'
Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'
Worldwide Experience in Training / Seminar / Workshop Deliveries:
Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston.
He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:

Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.
Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.
Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information post training support and fees applicable
Accreditions And Affliations

Data Analytics Workflows for Artificial Lift, Production and Facility Engineers

<div>
</div>
<section>
<div>
<h2><strong>About this Virtual Instructor Led Training (VILT)</strong></h2>
<p><span>This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system.</span></p>
<p><span>The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way.</span></p>
<p><span>With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed.</span></p>
<p><span>Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery.</span></p>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p><span>Upon completion of this VILT course, participants will be able to:</span></p>
<ul>
<li><span>Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues.</span></li>
<li><span>Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices.</span></li>
<li><span>Understand and analyze energy performance from main renewable energy systems.</span></li>
<li><span>Get equipped on the insights into forecasting models for solar energy.</span></li>
<li><span>Predict solar generation from weather forecasts using machine learning.</span></li>
<li><span>Explore operational aspects of a complex power system with variability from both the supply &amp; demand sides.</span></li>
<li><span>Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation.</span></li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p><span>Engineers, planners and operations professionals from the following organizations:</span></p>
<ul>
<li><span>Energy aggregators who would like to understand the system operations of renewable energy power plants</span></li>
<li><span>Renewable energy power system operator</span></li>
<li><span>Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations</span></li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Basic or Foundation</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Training Methods 

</div>
<div id="collapseThree">
<div>
<p><span>The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises.</span></p>
<p>Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total).</p>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p><strong>Your first expert course leader</strong> is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.</p>
<p>With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.</p>
<p><strong>Your second expert course leader </strong>is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch.</p>
<p>He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto.</p>
<p>Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin.</p>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information about post training coaching support and fees applicable for this.</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this Virtual Instructor Led Training (VILT)
This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system.
The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way.
With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed.
Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery.
Training Objectives
Upon completion of this VILT course, participants will be able to:
Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues.
Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices.
Understand and analyze energy performance from main renewable energy systems.
Get equipped on the insights into forecasting models for solar energy.
Predict solar generation from weather forecasts using machine learning.
Explore operational aspects of a complex power system with variability from both the supply & demand sides.
Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation.
Target Audience
Engineers, planners and operations professionals from the following organizations:
Energy aggregators who would like to understand the system operations of renewable energy power plants
Renewable energy power system operator
Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations
Course Level
Basic or Foundation
Training Methods
The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises.
Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total).
Trainer
Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.
With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.
Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch.
He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto.
Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin.
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information about post training coaching support and fees applicable for this.
Accreditions And Affliations

Large Scale Solar & Energy Storage - System Operations

<div>
</div>
<section>
<div>
<h2><strong>About this Virtual Instructor Led Training (VILT)</strong></h2>
<p>This Virtual Instructor Led Training (VILT) course presents advanced methodologies that implement demand response and energy conservation programs in light of the integration of new technologies, regulatory changes and the accelerated penetration of renewable energy resources.</p>
<p>This VILT course provides examples and case studies from North American and European jurisdictions covering the operational flexibilities on the demand side including requirements for new building codes to achieve zero net energy. The course describes a public agency's goals and objectives for conserving and otherwise reducing energy consumption and managing its demand for energy. This course presents the demand response implemented for economics and system security such as system balancing and relieving transmission congestion, or for system adequacy. The course also presents the principal attributes of conservation programs and the associated success criteria. In a system with increased penetration of renewable resources, demand response provides flexibility to system operators, helping them to maintain the reliability and the security of supply.</p>
<p>Demand response is presented as a competitive alternative to additional power sources, enhancing competition and liquidity in electricity markets. The unique characteristics are discussed from a local, consumer centric and also from a system perspective bringing to life the ever changing paradigm for delivery energy to customers. Interoperability aspects and standards are discussed, as well as the consumer centric paradigm of Transactive Energy with IOT enabled flexibilities at system level, distribution networks and microgrids.</p>
<p>The VILT course introduces the blockchain as a new line of defense against cyber threats and its increasing application in P2P transactions and renewable certificates. Our trainer's industry experience spans three decades with one of the largest Canadian utilities where she led or contributed to large operational studies and energy policies and decades of work with IEEE, NSERC and CIGRE. Our key expert also approaches to the cross sectional, interdisciplinary state of the art methodologies brings real life experience of recent industry developments.</p>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<ul>
<li>Innovative Digital Technologies</li>
<li>How systems Facilitate Operational Flexibility on the Demand Side</li>
<li>The Ecosystem of Demand Side Management Programs</li>
<li>Advanced Machine Learning techniques with examples from CAISO</li>
<li>Regulatory Policy Context and how to reduce regulatory barriers</li>
<li>Industry Examples from NERC and ENTSO</li>
<li>Relevant Industry standards: IEEE and IEC</li>
<li>Manage Congestion with Distributed Operational Flexibilities: Grid to Distribution Controls; examples from NERC (NA) and ENTSO (Europe)</li>
<li>Grid solutions with IEC 61850 communication protocols</li>
<li>Decentralized grid controls</li>
<li>The New Grid with accelerated V2G and Microgrids</li>
<li>How DSM is and will be applied in Your System: Examples and discussions</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<ul>
<li>Regulators and government agencies advising on public energy conservation programs</li>
<li>All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector</li>
<li>Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices</li>
<li>Any utility professional interested in understanding the new developments in the power industry</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Basic or Foundation</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Training Methods 

</div>
<div id="collapseThree">
<div>
<p>The VILT course will be delivered online in <strong>5 half-day sessions comprising 4 hours per day, with 2 x 10 minutes break per day</strong>, including time for lectures, discussion, quizzes and short classroom exercises.</p>
<p>Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total).</p>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p><strong>Your first expert course leader</strong> is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.</p>
<p>With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.</p>
<p><strong>Your second expert course leader </strong>is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch.</p>
<p>He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto.</p>
<p>Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin.</p>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information about post training coaching support and fees applicable for this.</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

About this Virtual Instructor Led Training (VILT)
This Virtual Instructor Led Training (VILT) course presents advanced methodologies that implement demand response and energy conservation programs in light of the integration of new technologies, regulatory changes and the accelerated penetration of renewable energy resources.
This VILT course provides examples and case studies from North American and European jurisdictions covering the operational flexibilities on the demand side including requirements for new building codes to achieve zero net energy. The course describes a public agency's goals and objectives for conserving and otherwise reducing energy consumption and managing its demand for energy. This course presents the demand response implemented for economics and system security such as system balancing and relieving transmission congestion, or for system adequacy. The course also presents the principal attributes of conservation programs and the associated success criteria. In a system with increased penetration of renewable resources, demand response provides flexibility to system operators, helping them to maintain the reliability and the security of supply.
Demand response is presented as a competitive alternative to additional power sources, enhancing competition and liquidity in electricity markets. The unique characteristics are discussed from a local, consumer centric and also from a system perspective bringing to life the ever changing paradigm for delivery energy to customers. Interoperability aspects and standards are discussed, as well as the consumer centric paradigm of Transactive Energy with IOT enabled flexibilities at system level, distribution networks and microgrids.
The VILT course introduces the blockchain as a new line of defense against cyber threats and its increasing application in P2P transactions and renewable certificates. Our trainer's industry experience spans three decades with one of the largest Canadian utilities where she led or contributed to large operational studies and energy policies and decades of work with IEEE, NSERC and CIGRE. Our key expert also approaches to the cross sectional, interdisciplinary state of the art methodologies brings real life experience of recent industry developments.
Training Objectives
Innovative Digital Technologies
How systems Facilitate Operational Flexibility on the Demand Side
The Ecosystem of Demand Side Management Programs
Advanced Machine Learning techniques with examples from CAISO
Regulatory Policy Context and how to reduce regulatory barriers
Industry Examples from NERC and ENTSO
Relevant Industry standards: IEEE and IEC
Manage Congestion with Distributed Operational Flexibilities: Grid to Distribution Controls; examples from NERC (NA) and ENTSO (Europe)
Grid solutions with IEC 61850 communication protocols
Decentralized grid controls
The New Grid with accelerated V2G and Microgrids
How DSM is and will be applied in Your System: Examples and discussions
Target Audience
Regulators and government agencies advising on public energy conservation programs
All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector
Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices
Any utility professional interested in understanding the new developments in the power industry
Course Level
Basic or Foundation
Training Methods
The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 x 10 minutes break per day, including time for lectures, discussion, quizzes and short classroom exercises.
Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total).
Trainer
Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.
With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.
Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch.
He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto.
Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin.
POST TRAINING COACHING SUPPORT (OPTIONAL)
To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.

Request for further information about post training coaching support and fees applicable for this.
Accreditions And Affliations

Demand Side Management - Integration of New Technologies, Regulatory Changes & Renewable Energy Resources

London

<h2>ITIL® 4 Specialist: Create, Deliver and Support: In-House Training</h2>
 <p>The ITIL® 4 Specialist: Create, Deliver, and Support module is part of the Managing Professional stream for ITIL® 4. Candidates need to pass the related certification exam for working towards the Managing Professional (MP) designation. </p>
 <p>This course is based on the ITIL® 4 Specialist: Create, Deliver, and Support exam specifications from AXELOS. With the help of ITIL® 4 concepts and terminology, exercises, and examples included in the course, candidates acquire the relevant knowledge required to pass the certification exam.</p><h3>What You Will Learn</h3>
 <p>The learning objectives of the course are based on the following learning outcomes of the ITIL® 4 Specialist: Create, Deliver, and Support exam specification: </p>
 <ul>
 <li>Understand how to plan and build a service value stream to create, deliver, and support services </li>
 <li>Know how relevant ITIL® practices contribute to the creation, delivery, and support across the SVS and value streams </li>
 <li>Know how to create, deliver, and support services</li>
 </ul><section>
                    <h3>Organization and Culture </h3> <ul> <li>Organizational Structures  </li> <li>Team Culture  </li> <li>Continuous Improvement </li> <li>Collaborative Culture  </li> <li>Customer-Oriented Mindset  </li> <li>Positive Communication </li> </ul> <h3>Effective Teams </h3> <ul> <li>Capabilities, Roles, and Competencies  </li> <li>Workforce Planning  </li> <li>Employee Satisfaction Management  </li> <li>Results-Based Measuring and Reporting </li> </ul> <h3>Information Technology to Create, Deliver, and Support Service  </h3> <ul> <li>Integration and Data Sharing  </li> <li>Reporting and Advanced Analytics  </li> <li>Collaboration and Workflow  </li> <li>Robotic Process Automation  </li> <li>Artificial Intelligence and Machine Learning  </li> <li>CI / CD  </li> <li>Information Model </li> </ul> <h3>Value Stream </h3> <ul> <li>Anatomy of a Value Stream  </li> <li>Designing a Value Stream </li> <li>Value Stream Mapping </li> </ul> <h3>Value Stream to Create, Deliver, and Support Services </h3> <ul> <li>Value Stream for Creation of a New Service  </li> </ul> <h3>Value Stream for User Support </h3> <ul> <li>Value Stream Model for Restoration of a Live Service  </li> </ul> <h3>Prioritize and Manage Work </h3> <ul> <li>Managing Queues and Backlogs  </li> <li>Shift-Left Approach </li> <li>Prioritizing Work  </li> </ul> <h3>Commercial and Sourcing Considerations </h3> <ul> <li>Build or Buy  </li> <li>Sourcing Models  </li> <li>Service Integration and Management</li> </ul>


                </section>

ITIL® 4 Specialist: Create, Deliver and Support: In-House Training
The ITIL® 4 Specialist: Create, Deliver, and Support module is part of the Managing Professional stream for ITIL® 4. Candidates need to pass the related certification exam for working towards the Managing Professional (MP) designation. 
This course is based on the ITIL® 4 Specialist: Create, Deliver, and Support exam specifications from AXELOS. With the help of ITIL® 4 concepts and terminology, exercises, and examples included in the course, candidates acquire the relevant knowledge required to pass the certification exam.
What You Will Learn
The learning objectives of the course are based on the following learning outcomes of the ITIL® 4 Specialist: Create, Deliver, and Support exam specification: 
Understand how to plan and build a service value stream to create, deliver, and support services
Know how relevant ITIL® practices contribute to the creation, delivery, and support across the SVS and value streams
Know how to create, deliver, and support services
Organization and Culture 
Organizational Structures
Team Culture
Continuous Improvement
Collaborative Culture
Customer-Oriented Mindset
Positive Communication
Effective Teams 
Capabilities, Roles, and Competencies
Workforce Planning
Employee Satisfaction Management
Results-Based Measuring and Reporting
Information Technology to Create, Deliver, and Support Service 
Integration and Data Sharing
Reporting and Advanced Analytics
Collaboration and Workflow
Robotic Process Automation
Artificial Intelligence and Machine Learning
CI / CD
Information Model
Value Stream 
Anatomy of a Value Stream
Designing a Value Stream
Value Stream Mapping
Value Stream to Create, Deliver, and Support Services 
Value Stream for Creation of a New Service
Value Stream for User Support 
Value Stream Model for Restoration of a Live Service
Prioritize and Manage Work 
Managing Queues and Backlogs
Shift-Left Approach
Prioritizing Work
Commercial and Sourcing Considerations 
Build or Buy
Sourcing Models
Service Integration and Management

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