Name: Data Analysis and Visualization with Microsoft Excel
Price: 55 GBP
Availability: InStock

Loughborough

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			<p>This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.</p>
			<div><i></i> 5 Days - 1 Exam</div>
			<div><i></i>  £595.00 incl. VAT</div>
			
			
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		<h3>Description</h3>
		<p></p><p>For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes hands-on activities for each topic area.</p>
<h3>Course Objectives: </h3>
<p>In this course, you will implement data science techniques in order to address business issues. You will:</p>
<p>• Use data science principles to address business issues. <br />• Apply the extract, transform, and load (ETL) process to prepare datasets. <br />• Use multiple techniques to analyze data and extract valuable insights. <br />• Design a machine learning approach to address business issues. <br />• Train, tune, and evaluate classification models. <br />• Train, tune, and evaluate regression and forecasting models. <br />• Train, tune, and evaluate clustering models. <br />• Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.  However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. </p>
<p>Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business.  This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.</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 data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science.</p>
<p>You should have also have experience with high-level programming languages like Python. Being comfortable using fundamental Python data science libraries like NumPy and pandas is highly recommended.</p>
<p>In addition to programming, you should also have experience working with databases, including querying languages like SQL. </p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4>Lesson 1: Addressing Business Issues with Data Science</h4>
<div>
<p>Topic A: Initiate a Data Science Project<br />Topic B: Formulate a Data Science Problem</p>
<h4>Lesson 2: Extracting, Transforming, and Loading Data</h4>
<p>Topic A: Extract Data <br />Topic B: Transform Data <br />Topic C: Load Data</p>
<h4>Lesson 3: Analyzing Data</h4>
<p>Topic A: Examine Data<br />Topic B: Explore the Underlying Distribution of Data <br />Topic C: Use Visualizations to Analyze Data<br />Topic D: Preprocess Data</p>
<h4>Lesson 4: Designing a Machine Learning Approach</h4>
<p>Topic A: Identify Machine Learning Concepts<br />Topic B: Test a Hypothesis</p>
</div>
<h4>Lesson 5: Developing Classification Models</h4>
<p>Topic A: Train and Tune Classification Models <br />Topic B: Evaluate Classification Models</p>
<h4>Lesson 6: Developing Regression Models</h4>
<p>Topic A: Train and Tune Regression Models <br />Topic B: Evaluate Regression Models</p>
<h4>Lesson 7: Developing Clustering Models</h4>
<p>Topic A: Train and Tune Clustering Models <br />Topic B: Evaluate Clustering Models</p>
<h4>Lesson 8: Finalizing a Data Science Project</h4>
<p>Topic A: Communicate Results to Stakeholders <br />Topic B: Demonstrate Models in a Web App <br />Topic C: Implement and Test Production Pipelines</p>
<p></p>

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.
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

For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes hands-on activities for each topic area.
Course Objectives: 
In this course, you will implement data science techniques in order to address business issues. You will:
• Use data science principles to address business issues. 
• Apply the extract, transform, and load (ETL) process to prepare datasets. 
• Use multiple techniques to analyze data and extract valuable insights. 
• Design a machine learning approach to address business issues. 
• Train, tune, and evaluate classification models. 
• Train, tune, and evaluate regression and forecasting models. 
• Train, tune, and evaluate clustering models. 
• Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.

Target Student

This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. 
Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.

Prerequisites

To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science.
You should have also have experience with high-level programming languages like Python. Being comfortable using fundamental Python data science libraries like NumPy and pandas is highly recommended.
In addition to programming, you should also have experience working with databases, including querying languages like SQL. 

Modules/Lessons

Lesson 1: Addressing Business Issues with Data Science
Topic A: Initiate a Data Science Project
Topic B: Formulate a Data Science Problem
Lesson 2: Extracting, Transforming, and Loading Data
Topic A: Extract Data 
Topic B: Transform Data 
Topic C: Load Data
Lesson 3: Analyzing Data
Topic A: Examine Data
Topic B: Explore the Underlying Distribution of Data 
Topic C: Use Visualizations to Analyze Data
Topic D: Preprocess Data
Lesson 4: Designing a Machine Learning Approach
Topic A: Identify Machine Learning Concepts
Topic B: Test a Hypothesis
Lesson 5: Developing Classification Models
Topic A: Train and Tune Classification Models 
Topic B: Evaluate Classification Models
Lesson 6: Developing Regression Models
Topic A: Train and Tune Regression Models 
Topic B: Evaluate Regression Models
Lesson 7: Developing Clustering Models
Topic A: Train and Tune Clustering Models 
Topic B: Evaluate Clustering Models
Lesson 8: Finalizing a Data Science Project
Topic A: Communicate Results to Stakeholders 
Topic B: Demonstrate Models in a Web App 
Topic C: Implement and Test Production Pipelines


Mpi Learning - Professional Learning And Development Provider

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Certified Data Science Practitioner

General Admission

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			<p>The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms.</p>
			<div><i></i> 120 minutes</div>
			<div><i></i>  £50.00 incl. VAT</div>
			
			
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		<h3>Description</h3>
		<p></p><p>The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improve and expand the success of the business.</p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4><span><strong>Lesson 1:</strong> Data Science Fundamentals</span></h4>
<p>Topic A: What is Data Science?<br />Topic B: Types of Data<br />Topic C: The Data Science Lifecycle</p>
<h4><span><strong>Lesson 2:</strong> Data Science Implementation</span></h4>
<p>Topic A: Data Acquisition and Preparation<br />Topic B: Data Modeling and Visualization<br />Topic C: Data Science Roles</p>
<h4><span><strong>Lesson 3:</strong> The Impact of Data Science</span></h4>
<p>Topic A: Benefits of Data Science<br />Topic B: Challenges of Data Science<br />Topic C: Business Use Cases for Data Science</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for business leaders and decision-makers, including C-level executives, project managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who want to increase their knowledge of and familiarity with concepts surrounding data science. Other individuals who want to know more about basic data science concepts are also candidates for this course.</p>
<p></p>

The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms.
120 minutes £50.00 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

The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improve and expand the success of the business.

Modules/Lessons

Lesson 1: Data Science Fundamentals
Topic A: What is Data Science?
Topic B: Types of Data
Topic C: The Data Science Lifecycle
Lesson 2: Data Science Implementation
Topic A: Data Acquisition and Preparation
Topic B: Data Modeling and Visualization
Topic C: Data Science Roles
Lesson 3: The Impact of Data Science
Topic A: Benefits of Data Science
Topic B: Challenges of Data Science
Topic C: Business Use Cases for Data Science

Target Student

This course is designed for business leaders and decision-makers, including C-level executives, project managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who want to increase their knowledge of and familiarity with concepts surrounding data science. Other individuals who want to know more about basic data science concepts are also candidates for this course.


The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms.

Data Science for Business Professionals

Medway

<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;">Overview</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This is an 8-hour course aimed to help you learn what is meant by Data Science, what it involves and how it is often done, then to complete a small practical project to use some of the techniques and to get an idea of whether this is something that you might want to take further.</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;">How you will learn</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will be coached and mentored to complete the<em fr-original-style="" style="box-sizing: border-box;"> CISCO Skills for All </em>online course<em fr-original-style="" style="box-sizing: border-box;"> "Introduction to Data Science"</em> over a series of 3 two-hour, one per week. sessions with an opportunity to continue the learning in between sessions.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Each week there will be a half-hour workshop introducing a data tool (spreadsheet, visualisation, story-telling)</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will choose a data set that interests you and, in an final 2 hour session, you will complete a small practical project with your chosen dataset and one or more of the tools introduced in previous weeks.</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;">Topics</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will find a list of topics covered in the online course here</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;">Achievements</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will earn CISCO badges</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Introduction to Data Science</li><li fr-original-style="" style="box-sizing: border-box;">Basics of Analytics</li><li fr-original-style="" style="box-sizing: border-box;">Data Collection</li><li fr-original-style="" style="box-sizing: border-box;">Artificial Intelligence and Machine Learning Concepts</li><li fr-original-style="" style="box-sizing: border-box;">Data Careers</li></ul><div fr-original-style="" style="box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">and a statement of achievement from futureCodersSE CIC, with a shared link to your project to add to your CV or LinkedIn profile.</span></div><div fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></div>

Overview
This is an 8-hour course aimed to help you learn what is meant by Data Science, what it involves and how it is often done, then to complete a small practical project to use some of the techniques and to get an idea of whether this is something that you might want to take further.
How you will learn
You will be mentored to complete the CISCO Skills for All online course "Introduction to Data Science" over a series of 4 two-hour, one per week. sessions with an opportunity to continue the learning in between sessions.
Each week there will be a half-hour workshop introducing a data tool (spreadsheet, visualisation, story-telling)
You will choose a data set that interests you and, in an final 2 hour session, you will complete a small practical project with your chosen dataset and one or more of the tools introduced in previous weeks.
Topics
You will find a list of topics covered in the online course here
Achievements
You will earn CISCO badges
Introduction to Data Science
Basics of Analytics
Data Collection
Artificial Intelligence and Machine Learning Concepts
Data Careers
and a statement of achievement from futureCodersSE CIC, with a shared link to your project to add to your CV or LinkedIn profile.

futureCoders SE

Data Storytelling

Learn the basics of Data Science, combining a supported #CISCO Skills for All online course with practical learning and a project to help consolidate the learning.

Introduction to Data Science

General admission

<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;">Overview</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This is an 8-hour course aimed to help you learn what is meant by Data Science, what it involves and how it is often done, then to complete a small practical project to use some of the techniques and to get an idea of whether this is something that you might want to take further.</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;">How you will learn</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will be coached and mentored to complete the<em fr-original-style="" style="box-sizing: border-box;"> CISCO Skills for All </em>online course<em fr-original-style="" style="box-sizing: border-box;"> "Introduction to Data Science"</em> over a series of 3 two-hour, one per week. sessions with an opportunity to continue the learning in between sessions.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Each week there will be an hour long workshop introducing a data tool (spreadsheet, visualisation, story-telling) and giving you practical exercises to do.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will choose a data set that interests you and, in an final 2 hour session, you will complete a small practical project with your chosen dataset and one or more of the tools introduced in previous weeks.</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;">Topics</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will find a list of topics covered in the online course here</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;">Achievements</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will earn CISCO badges</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Introduction to Data Science</li><li fr-original-style="" style="box-sizing: border-box;">Basics of Analytics</li><li fr-original-style="" style="box-sizing: border-box;">Data Collection</li><li fr-original-style="" style="box-sizing: border-box;">Artificial Intelligence and Machine Learning Concepts</li><li fr-original-style="" style="box-sizing: border-box;">Data Careers</li></ul><div fr-original-style="" style="box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">and a statement of achievement from futureCodersSE CIC, with a shared link to your project to add to your CV or LinkedIn profile.</span></div><div fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></div>

Overview
This is an 8-hour course aimed to help you learn what is meant by Data Science, what it involves and how it is often done, then to complete a small practical project to use some of the techniques and to get an idea of whether this is something that you might want to take further.
How you will learn
You will be coached and mentored to complete the CISCO Skills for All online course "Introduction to Data Science" over a series of 3 two-hour, one per week. sessions with an opportunity to continue the learning in between sessions.
Each week there will be an hour long workshop introducing a data tool (spreadsheet, visualisation, story-telling) and giving you practical exercises to do.
You will choose a data set that interests you and, in an final 2 hour session, you will complete a small practical project with your chosen dataset and one or more of the tools introduced in previous weeks.
Topics
You will find a list of topics covered in the online course here
Achievements
You will earn CISCO badges
Introduction to Data Science
Basics of Analytics
Data Collection
Artificial Intelligence and Machine Learning Concepts
Data Careers
and a statement of achievement from futureCodersSE CIC, with a shared link to your project to add to your CV or LinkedIn profile.

Introduction to Data Science - free for Medway residents

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

Machine Learning (ML)

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>
			
			<p>In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.</p>
			<div><i></i> 120 minutes</div>
			<div><i></i>  £50.00 incl. VAT</div>
			
			
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		<div></div>

		<div>
			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
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		<div>
			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
		</div>
	</div>
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        <div>
			
		</div>
				

	
		<h3>Description</h3>
		<p></p><p>In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider-it is a truly disruptive force, one that promises to deliver an entirely new level of results for all aspects of the business. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI.</p>
<p>Despite its promises, AI can seem like a daunting concept for business professionals. How can you hope to apply AI to your own business if you can't see beyond the vague buzzwords and hype? That's why this course was created: to give you the essential knowledge of AI you'll need to steer the business forward.</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is primarily designed for managers, business leaders, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>To ensure your success in this course, you should have foundational knowledge of business processes and general concepts. You should also have at least a basic understanding of information technology resources and systems, including networks, computers, and other electronic devices used in the enterprise.</p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4><span><strong>Lesson 1: AI Fundamentals</strong></span></h4>
<p>Topic A: AI Concepts<br />Topic B: Approaches to Machine Learning and Deep Learning</p>
<h4><span><strong>Lesson 2: AI Implementations</strong></span></h4>
<p>Topic A: Data Science<br />Topic B: Search Engines</p>
<h4><span><strong>Lesson 2: AI Implementations (cont.)</strong></span></h4>
<p>Topic C: Natural Language Processing<br />Topic D: Computer Vision<br />Topic E: Robotics</p>
<h4><span><strong>Lesson 4: The Impact of AI</strong></span></h4>
<p>Topic A: Benefits of AI<br />Topic B: Challenges of AI<br />Topic C: Business Use Cases for AI</p>
<p></p>

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.
120 minutes £50.00 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

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider-it is a truly disruptive force, one that promises to deliver an entirely new level of results for all aspects of the business. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI.
Despite its promises, AI can seem like a daunting concept for business professionals. How can you hope to apply AI to your own business if you can't see beyond the vague buzzwords and hype? That's why this course was created: to give you the essential knowledge of AI you'll need to steer the business forward.

Target Student

This course is primarily designed for managers, business leaders, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course.

Prerequisites

To ensure your success in this course, you should have foundational knowledge of business processes and general concepts. You should also have at least a basic understanding of information technology resources and systems, including networks, computers, and other electronic devices used in the enterprise.

Modules/Lessons

Lesson 1: AI Fundamentals
Topic A: AI Concepts
Topic B: Approaches to Machine Learning and Deep Learning
Lesson 2: AI Implementations
Topic A: Data Science
Topic B: Search Engines
Lesson 2: AI Implementations (cont.)
Topic C: Natural Language Processing
Topic D: Computer Vision
Topic E: Robotics
Lesson 4: The Impact of AI
Topic A: Benefits of AI
Topic B: Challenges of AI
Topic C: Business Use Cases for AI


Online Course Marketing

Business Analytics & Intelligence

Generative AI

Business Information Technology

Microsoft AI-900

AI (Artificial Intelligence)

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

AI For Leaders

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			<p>Data Ethics for Business Professionals is designed for individuals who are seeking to demonstrate an understanding of the ethical uses of data in business settings.</p>
			<div><i></i> 6 hours or 3 x 90 min sessions</div>
			<div><i></i>  £45.00 incl. VAT</div>
			
			
		</div>
	</div>

	

	<div id="filters">
		
		
	</div>

	

    <div>

		
		 
		

		<div></div>

		<div>
			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
		</div>

		<div>
			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
		</div>
	</div>
	<div></div>
	
		
        <div>
			
		</div>
				

	
		<h3>Description</h3>
		<p></p><p><span>This course empowers professionals to identify sources of ethical risk and move beyond transparency to understand all ethical principles while balancing business considerations of ethically driven technology.</span></p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4>Overview</h4>
<p>The power of extracting value from data utilizing Artificial Intelligence, Data Science and Machine Learning exposes the learning differences between humans and machines. Humans can apply ethical principles throughout the decision-making process to avoid discrimination, societal harm, and marginalization to maintain and even enhance acceptable norms. Machines make decisions autonomously. So how do we apply ethical principles to data driven technology? This course provides business professionals and consumers of technology core concepts of ethical principles, how they can be applied to emerging data driven technologies and the impact to an organization which ignores ethical use of technology.</p>
<h4>Course Length:</h4>
<p>6 hours instructional time Content is designed to be presented as a full day class, or in three 90-minute sessions by lesson.</p>
<h4>Course Content:</h4>
<p>Each lesson includes activities, indicated in orange and may include resources for learners to integrate ethical practices into their own organization, indicated in blue.</p>
<h4>Introduction to Data Ethics</h4>
<p>Define Ethics <br />Define Data <br />Define Data Ethics <br />Principles of Data Ethics <br />The Case for Data Ethics<br />Identifying Ethical Issues</p>
<h4>Ethical Principles</h4>
<p>Ethical Frameworks <br />Applying Ethical Frameworks <br />Privacy, Fairness, and Safety <br />Applying Privacy, Fairness, and Safety Principles <br />Algorithms and Human-Centered Values <br />Discussing True and False Positives and Negatives <br />Discussing Accuracy and Precision <br />Discussing Correlation and Causation <br />Transparency and Explainability: The Black Box Problem <br />Discussing Black Box Parallels <br />Inclusive Growth, Sustainable Development, and Well-Being <br />Examining a Tech for Good Organization <br />Improving Ethical Data Practices</p>
<h4>Sources of Ethical Risk</h4>
<p>Bias and Discrimination <br />Case Study: Allegheny Family Screening Tool <br />Data Surveillance <br />Safety and Security <br />Case Study: PredPol</p>
<h4>Business Considerations</h4>
<p>Data Legislation <br />Manage the Effects of Data <br />Case Study <br />Embed Organizational Values in the Data Value Chain <br />Building a Data Ethics Culture/Code of Ethics</p>
<h4>Exam</h4>
<p><span>A Data Ethics Business Professional is an individual who has demonstrated foundational knowledge of the ethical use of data in emerging technologies in a business. A credential holder is able to identify, explain, and document how organizations identify ethical principles and considerations, understand sources of risk, and explain how businesses can create sustainable, ethical decision-making processes.</span></p>
<p><span>Exam Details: 40 Mins, Multiple Choice Online Assessment. </span></p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for business leaders and decision makers, including C-level executives, project and product managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who have a vested interest in the representation of ethical values in technology solutions. Other individuals who want to know more about data ethics are also candidates for this course.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>To ensure your success in this course, you should have a working knowledge of general business concepts and practices. You should also have a basic understanding of Artificial Intelligence and or Data Science.</p>
<p></p>

Data Ethics for Business Professionals is designed for individuals who are seeking to demonstrate an understanding of the ethical uses of data in business settings.
6 hours or 3 x 90 min sessions £45.00 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

This course empowers professionals to identify sources of ethical risk and move beyond transparency to understand all ethical principles while balancing business considerations of ethically driven technology.

Modules/Lessons

Overview
The power of extracting value from data utilizing Artificial Intelligence, Data Science and Machine Learning exposes the learning differences between humans and machines. Humans can apply ethical principles throughout the decision-making process to avoid discrimination, societal harm, and marginalization to maintain and even enhance acceptable norms. Machines make decisions autonomously. So how do we apply ethical principles to data driven technology? This course provides business professionals and consumers of technology core concepts of ethical principles, how they can be applied to emerging data driven technologies and the impact to an organization which ignores ethical use of technology.
Course Length:
6 hours instructional time Content is designed to be presented as a full day class, or in three 90-minute sessions by lesson.
Course Content:
Each lesson includes activities, indicated in orange and may include resources for learners to integrate ethical practices into their own organization, indicated in blue.
Introduction to Data Ethics
Define Ethics 
Define Data 
Define Data Ethics 
Principles of Data Ethics 
The Case for Data Ethics
Identifying Ethical Issues
Ethical Principles
Ethical Frameworks 
Applying Ethical Frameworks 
Privacy, Fairness, and Safety 
Applying Privacy, Fairness, and Safety Principles 
Algorithms and Human-Centered Values 
Discussing True and False Positives and Negatives 
Discussing Accuracy and Precision 
Discussing Correlation and Causation 
Transparency and Explainability: The Black Box Problem 
Discussing Black Box Parallels 
Inclusive Growth, Sustainable Development, and Well-Being 
Examining a Tech for Good Organization 
Improving Ethical Data Practices
Sources of Ethical Risk
Bias and Discrimination 
Case Study: Allegheny Family Screening Tool 
Data Surveillance 
Safety and Security 
Case Study: PredPol
Business Considerations
Data Legislation 
Manage the Effects of Data 
Case Study 
Embed Organizational Values in the Data Value Chain 
Building a Data Ethics Culture/Code of Ethics
Exam
A Data Ethics Business Professional is an individual who has demonstrated foundational knowledge of the ethical use of data in emerging technologies in a business. A credential holder is able to identify, explain, and document how organizations identify ethical principles and considerations, understand sources of risk, and explain how businesses can create sustainable, ethical decision-making processes.
Exam Details: 40 Mins, Multiple Choice Online Assessment. 

Target Student

This course is designed for business leaders and decision makers, including C-level executives, project and product managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who have a vested interest in the representation of ethical values in technology solutions. Other individuals who want to know more about data ethics are also candidates for this course.

Prerequisites

To ensure your success in this course, you should have a working knowledge of general business concepts and practices. You should also have a basic understanding of Artificial Intelligence and or Data Science.


Data Ethics for Business Professionals is designed for individuals who are seeking to demonstrate an understanding of the ethical uses of data in business settings.

Data Ethics for Business Professionals

<div>
</div>
<section>
<div>
<h2><strong>About this Virtual Instructor Led Training (VILT)</strong></h2>
<p>The energy industry has started its journey to be more data centric by embracing the industry 4.0 concept. As a result, data management - which was considered until recently as a back-office service to support geoscience, reservoir management, engineering, production and maintenance - is now given the spotlight!</p>
<p>To become an active stakeholder in this important transition in E&amp;P data management, it is necessary to understand the new technical opportunities offered by the Cloud, Artificial Intelligence and how data governance can pave the way towards more reliable and resilient processes within E&amp;P domain.</p>
<p>Several key questions that need to be addressed:</p>
<ol>
<li>Why place more focus on data assets?</li>
<li>Is data management just about serving geoscientists or engineers with fresh data?</li>
<li>What is the value of data management in the E&amp;P sector for decision making?</li>
<li>How to convince the data consumers that the data we provide is reliable?</li>
<li>Is the data architecture of my organization appropriate and sustainable?</li>
</ol>
<p>The purpose of this 5 half-day Virtual Instructor Led Training (VILT) course is to present the data challenges facing the energy organizations today and see how they practically solve them. The backbone of this course is based on the <strong>DAMA Book of Knowledge for Data Management</strong>. The main data management activities are described in sequence with a particular focus on recent technological developments.</p>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p>Upon completion of this VILT course, the participants will be able to:</p>
<ul>
<li>Understand why the data asset is now considered as a main asset by energy organizations</li>
<li>Appreciate the importance of data governance and become an active stakeholder of it</li>
<li>Understand the architecture and implementation of data structure in their professional environment</li>
<li>Get familiarized with the more important data management activities such as data security and data quality</li>
<li>Integrate their subsurface and surface engineering skills with the data managements concepts</li>
</ul>
<p>This VILT course is unique on several points:</p>
<ul>
<li>All notions are explained by some short presentations. For each of them, a set of video, exercises, quizzes will be provided to help develop an engaging experience between the trainer and the participants</li>
<li>A pre-course questionnaire to help the trainer focus on the participants' needs and learning objectives</li>
<li>A detailed reference manual</li>
<li>A lexicon of terms for data-management</li>
<li>Limited class size to encourage the interactivity</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p>This VILT course is intended for:</p>
<ul>
<li>Junior/new data managers</li>
<li>Geoscientists</li>
<li>Reservoir engineers</li>
<li>Producers</li>
<li>Maintenance specialists</li>
<li>Construction specialists</li>
<li>Human resources</li>
<li>Legal</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-days consisting 4 hours per day</strong>, with 2 breaks of 10 minutes per day.</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>Your expert course leader is a geologist by education who has dedicated his career to subsurface data management services. In 2016, he initiated a tech startup dedicated to Data Management using Artificial Intelligence (AI) tools. He is heavily involved in developing business plans, pricing strategies, partnerships, marketing and SEO, and is the co-author of several Machine Learning publications. He also delivers training on Data Management and Data Science to students and professionals.</p>
<p>Based in France, he was formerly Vice President, Sales &amp; Marketing at CGG where he was in charge of the Data Management Services strategy, Sales Manager at Spie O&amp;G Services where he initiated the Geoscience technical assistance activities and Product Manager of interactive seismic inversion software design and marketing at Paradigm.</p>
<p> </p>
<p> </p>
<p> </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)
The energy industry has started its journey to be more data centric by embracing the industry 4.0 concept. As a result, data management - which was considered until recently as a back-office service to support geoscience, reservoir management, engineering, production and maintenance - is now given the spotlight!
To become an active stakeholder in this important transition in E&P data management, it is necessary to understand the new technical opportunities offered by the Cloud, Artificial Intelligence and how data governance can pave the way towards more reliable and resilient processes within E&P domain.
Several key questions that need to be addressed:
Why place more focus on data assets?
Is data management just about serving geoscientists or engineers with fresh data?
What is the value of data management in the E&P sector for decision making?
How to convince the data consumers that the data we provide is reliable?
Is the data architecture of my organization appropriate and sustainable?
The purpose of this 5 half-day Virtual Instructor Led Training (VILT) course is to present the data challenges facing the energy organizations today and see how they practically solve them. The backbone of this course is based on the DAMA Book of Knowledge for Data Management. The main data management activities are described in sequence with a particular focus on recent technological developments.
Training Objectives
Upon completion of this VILT course, the participants will be able to:
Understand why the data asset is now considered as a main asset by energy organizations
Appreciate the importance of data governance and become an active stakeholder of it
Understand the architecture and implementation of data structure in their professional environment
Get familiarized with the more important data management activities such as data security and data quality
Integrate their subsurface and surface engineering skills with the data managements concepts
This VILT course is unique on several points:
All notions are explained by some short presentations. For each of them, a set of video, exercises, quizzes will be provided to help develop an engaging experience between the trainer and the participants
A pre-course questionnaire to help the trainer focus on the participants' needs and learning objectives
A detailed reference manual
A lexicon of terms for data-management
Limited class size to encourage the interactivity
Target Audience
This VILT course is intended for:
Junior/new data managers
Geoscientists
Reservoir engineers
Producers
Maintenance specialists
Construction specialists
Human resources
Legal
Course Level
Basic or Foundation
Training Methods
The VILT course will be delivered online in 5 half-days consisting 4 hours per day, with 2 breaks of 10 minutes per day.
Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total).
Trainer
Your expert course leader is a geologist by education who has dedicated his career to subsurface data management services. In 2016, he initiated a tech startup dedicated to Data Management using Artificial Intelligence (AI) tools. He is heavily involved in developing business plans, pricing strategies, partnerships, marketing and SEO, and is the co-author of several Machine Learning publications. He also delivers training on Data Management and Data Science to students and professionals.
Based in France, he was formerly Vice President, Sales & Marketing at CGG where he was in charge of the Data Management Services strategy, Sales Manager at Spie O&G Services where he initiated the Geoscience technical assistance activities and Product Manager of interactive seismic inversion software design and marketing at Paradigm.
 
 
 
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

Renewable Energy

Oil & Gas

Fundamentals of E&P Data Management

<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)

</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
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>
			
			<p>This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data and visualize data and insights using advanced visualizations in charts and dashboards in Excel.</p>
			<div><i></i> 2 Days</div>
			<div><i></i>  £55.00 incl. VAT</div>
			
			
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	</div>

	

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		<h3>Description</h3>
		<p></p><p>Technology and the data that it both collects and makes accessible is now interwoven with businesses and lives. The era of "big data" has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and a competitive advantage.</p>
<p>Analyzing data to find issues, insights, and opportunities is now a critical part of many job roles. Beyond the analysis, data analysts in all job roles must be able to effectively present and communicate their findings in visually compelling ways.</p>
<p>Microsoft® Excel® is designed for this purpose. Excel can connect to a wide range of data sources, perform robust data analysis, create diverse and robust data-backed visualizations to show insights and trends, and create reports. These capabilities enable people who use Excel for data analysis to turn data into thoughtful action.</p>
<h4>Course Objectives:</h4>
<p>In this course, you will analyze and visualize data using Microsoft Excel and associated tools. You will:</p>
<ul>
<li>Perform data analysis fundamentals.</li>
<li>Visualize data with Excel.</li>
<li>Analyze data with formulas and functions.</li>
<li>Analyze data with PivotTables.</li>
<li>Present visual insights with dashboards in Excel.</li>
<li>Create geospatial visualization with Excel.</li>
<li>Perform statistical analysis.</li>
<li>Get and transform data.</li>
<li>Model and analyze data with Power Pivot.</li>
<li>Present insights with reports.</li>
</ul>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4><strong>Lesson 1: </strong>Data Analysis Fundamentals</h4>
<p>Topic A: Introduction to Data Science<br />Topic B: Create and Modify Tables<br />Topic C: Sort and Filter Data</p>
<h4><strong>Lesson 2: </strong>Visualizing Data with Excel</h4>
<p>Topic A: Visualize Data with Charts<br />Topic B: Modify and Format Charts<br />Topic C: Apply Best Practices in Chart Design</p>
<h4><strong>Lesson 3: </strong>Analyzing Data with Formulas and Functions</h4>
<p>Topic A: Analyze Data with Formulas and Named Ranges<br />Topic B: <span>Analyze Data with Functions<br /></span>Topic C: <span>Implement Data Validation, Forms, and Controls<br /></span>Topic D: <span>Create Conditional Visualizations with Lookup Functions</span></p>
<h4><strong>Lesson 4: </strong>Analyzing Data with PivotTables</h4>
<p>Topic A: Create a PivotTable<br />Topic B: Analyze PivotTable Data</p>
<h4>Lesson 5: Presenting Visual Insights with Dashboards in Excel</h4>
<p>Topic A: Visualize Data with PivotCharts<br />Topic B: Filter Data Using Slicers and Timelines<br />Topic C: <span>Create a Dashboard in Excel</span></p>
<h4><strong>Lesson 6: </strong>Creating Geospatial Visualizations with Excel</h4>
<p>Topic A: Create Map Charts in Excel<br />Topic B: Customize Map Charts in Excel</p>
<h4><strong>Lesson 7: </strong>Performing Statistical Analysis</h4>
<p>Topic A: Visualize Trendlines and Sparklines with Excel<br />Topic B: Analyze Data with the Data Analysis ToolPak</p>
<h4><strong>Lesson 8: </strong>Getting and Transforming Data</h4>
<p>Topic A: Connect to Data with Queries<br />Topic B: Clean and Combine Data<br />Topic C: Shape and Transform Data</p>
<h4><strong>Lesson 9: </strong>Modeling and Analyzing Data with Power Pivot</h4>
<p>Topic A: Install Power Pivot in Excel<br />Topic B: Create Data Models with Power Pivot<br />Topic C: Create Power Pivots<br /><span>Topic D: </span><span>Perform Advanced Data Analysis and Visualization</span></p>
<h4>Lesson 10: Presenting Insights with Reports</h4>
<p>Topic A: Plan a Report<br />Topic B: Create a Report</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p><span>To ensure success, you should have baseline skill using Microsoft Excel worksheets, particularly in creating workbooks with formulas and functions.</span></p>
<h4>Course-specific Technical Requirements</h4>
<h4>Hardware:</h4>
<p>For this course, you will need one computer for each student and one for the instructor. Each computer will need the following minimum hardware configurations:</p>
<ul>
<li>1 gigahertz (GHz) 64-bit (x64) processor.</li>
<li>4 gigabytes (GB) of Random Access Memory (RAM).</li>
<li>32 GB available storage space.</li>
<li>Monitor capable of a screen resolution of at least 1,024 Ã 768 pixels, at least a 256-color display, and a video adapter with at least 4 MB of memory.</li>
<li>Bootable DVD-ROM or USB drive.</li>
<li>Keyboard and mouse or a compatible pointing device.</li>
<li>Fast Ethernet (100 Mb/s) adapter or faster and cabling to connect to the classroom network.</li>
<li>IP addresses that do not conflict with other portions of your network.</li>
<li>Internet access (contact your local network administrator).</li>
<li>(Instructor computer only) A display system to project the instructor's computer screen.</li>
</ul>
<h4>Software:</h4>
<ul>
<li>Microsoft® Office Professional Plus 2019 or Office 365â¢</li>
<li>Microsoft® Windows® 10 Professional or Enterprise</li>
</ul>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p><span>This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data, and visualize data and insights using advanced visualizations in charts and dashboards in Excel.</span></p>
<p></p>

This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data and visualize data and insights using advanced visualizations in charts and dashboards in Excel.
2 Days £55.00 incl. VAT
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Description

Technology and the data that it both collects and makes accessible is now interwoven with businesses and lives. The era of "big data" has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and a competitive advantage.
Analyzing data to find issues, insights, and opportunities is now a critical part of many job roles. Beyond the analysis, data analysts in all job roles must be able to effectively present and communicate their findings in visually compelling ways.
Microsoft® Excel® is designed for this purpose. Excel can connect to a wide range of data sources, perform robust data analysis, create diverse and robust data-backed visualizations to show insights and trends, and create reports. These capabilities enable people who use Excel for data analysis to turn data into thoughtful action.
Course Objectives:
In this course, you will analyze and visualize data using Microsoft Excel and associated tools. You will:
Perform data analysis fundamentals.
Visualize data with Excel.
Analyze data with formulas and functions.
Analyze data with PivotTables.
Present visual insights with dashboards in Excel.
Create geospatial visualization with Excel.
Perform statistical analysis.
Get and transform data.
Model and analyze data with Power Pivot.
Present insights with reports.

Modules/Lessons

Lesson 1: Data Analysis Fundamentals
Topic A: Introduction to Data Science
Topic B: Create and Modify Tables
Topic C: Sort and Filter Data
Lesson 2: Visualizing Data with Excel
Topic A: Visualize Data with Charts
Topic B: Modify and Format Charts
Topic C: Apply Best Practices in Chart Design
Lesson 3: Analyzing Data with Formulas and Functions
Topic A: Analyze Data with Formulas and Named Ranges
Topic B: Analyze Data with Functions
Topic C: Implement Data Validation, Forms, and Controls
Topic D: Create Conditional Visualizations with Lookup Functions
Lesson 4: Analyzing Data with PivotTables
Topic A: Create a PivotTable
Topic B: Analyze PivotTable Data
Lesson 5: Presenting Visual Insights with Dashboards in Excel
Topic A: Visualize Data with PivotCharts
Topic B: Filter Data Using Slicers and Timelines
Topic C: Create a Dashboard in Excel
Lesson 6: Creating Geospatial Visualizations with Excel
Topic A: Create Map Charts in Excel
Topic B: Customize Map Charts in Excel
Lesson 7: Performing Statistical Analysis
Topic A: Visualize Trendlines and Sparklines with Excel
Topic B: Analyze Data with the Data Analysis ToolPak
Lesson 8: Getting and Transforming Data
Topic A: Connect to Data with Queries
Topic B: Clean and Combine Data
Topic C: Shape and Transform Data
Lesson 9: Modeling and Analyzing Data with Power Pivot
Topic A: Install Power Pivot in Excel
Topic B: Create Data Models with Power Pivot
Topic C: Create Power Pivots
Topic D: Perform Advanced Data Analysis and Visualization
Lesson 10: Presenting Insights with Reports
Topic A: Plan a Report
Topic B: Create a Report

Prerequisites

To ensure success, you should have baseline skill using Microsoft Excel worksheets, particularly in creating workbooks with formulas and functions.
Course-specific Technical RequirementsHardware:
For this course, you will need one computer for each student and one for the instructor. Each computer will need the following minimum hardware configurations:
1 gigahertz (GHz) 64-bit (x64) processor.
4 gigabytes (GB) of Random Access Memory (RAM).
32 GB available storage space.
Monitor capable of a screen resolution of at least 1,024 Ã 768 pixels, at least a 256-color display, and a video adapter with at least 4 MB of memory.
Bootable DVD-ROM or USB drive.
Keyboard and mouse or a compatible pointing device.
Fast Ethernet (100 Mb/s) adapter or faster and cabling to connect to the classroom network.
IP addresses that do not conflict with other portions of your network.
Internet access (contact your local network administrator).
(Instructor computer only) A display system to project the instructor's computer screen.
Software:
Microsoft® Office Professional Plus 2019 or Office 365â¢
Microsoft® Windows® 10 Professional or Enterprise

Target Student

This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data, and visualize data and insights using advanced visualizations in charts and dashboards in Excel.


This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data and visualize data and insights using advanced visualizations in charts and dashboards in Excel.

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