Name: AI For Leaders
Price: 50 GBP
Availability: InStock

Loughborough

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

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

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

Modules/Lessons

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

Prerequisites

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

Target Student

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


Mpi Learning - Professional Learning And Development Provider

Machine Learning (ML)

NLP Practitioner

Trainers Course

Azure Machine Learning

Microsoft AI-900

AI (Artificial Intelligence)

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

Certified Artificial Intelligence Practitioner

General Admission

London

<p>This course will allow you to explore the potential of self-service business intelligence using Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and  data Modelling, to create Visualizations, and publish Reports to different platforms<br />.</p> <p><strong>Course Objectives</strong></p> <p>At the end of this course you will be able to:</p> <ul> <li>Connect to data from different sources.</li><li>Use the Query Editor</li><li>Perform Power BI desktop data Shaping and Transformation.</li><li>Create Power BI desktop Modelling.</li><li>Create Power BI desktop Visualizations and Reports.</li></ul> <p>' 1 year email support service</p> <p>Take a closer look at the <strong>consistent excellent feedback from our growing corporate clients</strong> visiting our site <em><strong>ms-officetraining co uk</strong></em></p> <p>With more than 20 years experience, we deliver courses on all levels of the Desktop version of <strong>Microsoft Office and Office 365</strong>; ranging from Beginner, Intermediate, Advanced to the VBA level and Business Intelligence.</p> <p>Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering<strong> public, one to one, tailored and bespoke courses.</strong></p> <ul> <li><strong>Our competitive rates <strong>start from £550.00 per day of training</strong></strong></li></ul> <p><strong><strong>Tailored training courses:</strong></strong></p> <p>You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs.</p> <p>Please visit our site (ms-officetraining co uk) to get a feel of the excellent feedback our courses have had and look at other courses you might be interested in.</p><p><strong>Introduction to Power BI</strong></p> <ul> <li>Power BI Jargon explained</li><li>A quick look at Power BI Desktop</li><li>A quick look at the Power BI service</li><li>Helpful resources</li></ul> <p><strong>Power BI and Excel</strong></p> <ul> <li>Introduction to using Excel data in Power BI</li><li>Upload Excel data to Power BI</li><li>Import Power View and Power Pivot to Power BI</li></ul> <p><strong>Getting started with Power BI Desktop</strong></p> <ul> <li>Overview of Power BI Desktop</li><li>Accessing Help and Helpful resources</li><li>Connect to data sources in Power BI Desktop</li></ul> <p><strong>Shaping and Transforming Data with Query Editor</strong></p> <ul> <li>Introduction to the Query Editor</li><li>Data Sources Power BI Desktop can Connect to</li><li>Introduction to Steps and M code</li><li>Combining Data Using Merge and Append Queries</li><li>Data Type Properties</li><li>Working with Delimiters</li><li>Clean and transform your data with the Query Editor</li><li>Text Specific Transformation Tools</li><li>Number Specific Transformation Tools</li><li>Date Specific Transformation Tools</li><li>Split and Merge columns</li><li>Creating an Index Column</li><li>Adding Conditional Columns</li><li>Columns From Examples</li><li>Grouping and Aggregating data</li><li>Pivoting and Unpivoting</li><li>Using filters</li></ul> <p><strong>Modeling the data</strong></p> <ul> <li>Introduction to modeling your data</li><li>How to manage your data relationships</li><li>Create calculated columns</li><li>Optimizing data models</li><li>Create calculated measures</li><li>Show Values As and Quick Measures</li><li>Create calculated tables</li><li>Explore your time-based data</li><li>Introduction to DAX</li><li>DAX calculation types</li><li>DAX functions</li></ul> <p><strong>Visualizations</strong></p> <ul> <li>Introduction to visuals in Power BI</li><li>Create and customize simple visualizations</li><li>Modify colors in charts and visuals</li><li>Shapes, text boxes, and images</li><li>Page layout and formatting</li><li>Group interactions among visualizations</li><li>Visual hierarchies and drill-down</li><li>Using custom visualizations</li><li>Create a KPI Visualization</li><li>Geo-Data and Maps</li></ul> <p><strong>Reports, Publishing and Sharing</strong></p> <ul> <li>Introduction to the Power BI service</li><li>Quick insights in Power BI</li><li>Create and configure a dashboard</li><li>Ask questions of your data with natural language</li><li>Create custom Q&amp;A suggestions</li><li>Share dashboards with your organization</li><li>Introduction to content packs, security, and groups</li><li>Publish Power BI Desktop reports</li><li>Print and export dashboards and reports</li><li>Create groups in Power BI</li><li>Use content packs</li><li>Update content packs</li><li>Publish to web</li></ul><h2>
        
            Who is this course for?
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                             <p>This course facilitates you with knowledge on the potential for Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, and to create  Visualizations, and publish Reports to different platforms.</p> 
                        </div><h2>
        
            Requirements
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p>Before attending this course, delegates should have:<br />- A general knowledge of database concepts (fields, records and relationships)<br />- Familiarity with Excel.</p> 
                        </div><h2>
        
            Career path
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>Business Intelligence<br /><br />Data Analysis<br /><br />ETL &amp; Data Warehousing</p> 
                        </div>

This course will allow you to explore the potential of self-service business intelligence using Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, to create Visualizations, and publish Reports to different platforms
.
Course Objectives
At the end of this course you will be able to:
Connect to data from different sources.
Use the Query Editor
Perform Power BI desktop data Shaping and Transformation.
Create Power BI desktop Modelling.
Create Power BI desktop Visualizations and Reports.
' 1 year email support service
Take a closer look at the consistent excellent feedback from our growing corporate clients visiting our site ms-officetraining co uk
With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level and Business Intelligence.
Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses.
Our competitive rates start from £550.00 per day of training
Tailored training courses:
You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs.
Please visit our site (ms-officetraining co uk) to get a feel of the excellent feedback our courses have had and look at other courses you might be interested in.
Introduction to Power BI
Power BI Jargon explained
A quick look at Power BI Desktop
A quick look at the Power BI service
Helpful resources
Power BI and Excel
Introduction to using Excel data in Power BI
Upload Excel data to Power BI
Import Power View and Power Pivot to Power BI
Getting started with Power BI Desktop
Overview of Power BI Desktop
Accessing Help and Helpful resources
Connect to data sources in Power BI Desktop
Shaping and Transforming Data with Query Editor
Introduction to the Query Editor
Data Sources Power BI Desktop can Connect to
Introduction to Steps and M code
Combining Data Using Merge and Append Queries
Data Type Properties
Working with Delimiters
Clean and transform your data with the Query Editor
Text Specific Transformation Tools
Number Specific Transformation Tools
Date Specific Transformation Tools
Split and Merge columns
Creating an Index Column
Adding Conditional Columns
Columns From Examples
Grouping and Aggregating data
Pivoting and Unpivoting
Using filters
Modeling the data
Introduction to modeling your data
How to manage your data relationships
Create calculated columns
Optimizing data models
Create calculated measures
Show Values As and Quick Measures
Create calculated tables
Explore your time-based data
Introduction to DAX
DAX calculation types
DAX functions
Visualizations
Introduction to visuals in Power BI
Create and customize simple visualizations
Modify colors in charts and visuals
Shapes, text boxes, and images
Page layout and formatting
Group interactions among visualizations
Visual hierarchies and drill-down
Using custom visualizations
Create a KPI Visualization
Geo-Data and Maps
Reports, Publishing and Sharing
Introduction to the Power BI service
Quick insights in Power BI
Create and configure a dashboard
Ask questions of your data with natural language
Create custom Q&A suggestions
Share dashboards with your organization
Introduction to content packs, security, and groups
Publish Power BI Desktop reports
Print and export dashboards and reports
Create groups in Power BI
Use content packs
Update content packs
Publish to web
 Who is this course for? Who is this course for? 
This course facilitates you with knowledge on the potential for Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, and to create Visualizations, and publish Reports to different platforms.
 Requirements Requirements 
Before attending this course, delegates should have:
- A general knowledge of database concepts (fields, records and relationships)
- Familiarity with Excel.
 Career path Career path 
Business Intelligence

Data Analysis

ETL & Data Warehousing

Microsoft Office Training

Powerbi

Microsoft Power Apps

Business Analytics & Intelligence

Microsoft Power BI

Microsoft Power Platform

Microsoft BI

Microsoft Power BI Desktop In-company (now with live online classes)

<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>
			
			
		</div>
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		<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>
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        <div>
			
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		<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


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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.

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