Name: Clustering and Classification with Machine Learning in Python
Price: 135.99 GBP
Availability: InStock

<p>Did you know that Microsoft Excel is the most widely used spreadsheet software in the world, with over 750 million users? With its advanced features and functions, Excel has become an essential tool for businesses and organisations across industries. In fact, 81% of businesses use Excel for budgeting and financial analysis, while 71% of businesses use it for data analysis and reporting. That's why advanced Excel skills are in high demand and can significantly boost your career prospects.</p><p>If you're looking to enhance your Excel skills and take your career to the next level, look no further than our Microsoft Excel Advanced at QLS Level 7 bundle. This exclusive bundle features two QLS-endorsed courses, including Excel Must Know Formulas and Functions and Introduction to Excel Data Tools and Data Management, as well as five relevant CPD QS-accredited courses.</p><p>The QLS-endorsed courses offer hardcopy certificates upon completion, giving you tangible proof of your expertise. Meanwhile, the CPD QS-accredited courses provide knowledge and insights that you can immediately apply to your work. From Excel Data Analysis to Excel Vlookup, Xlookup, Match and Index, Dynamic Excel Gantt Chart and Timelines, and Microsoft Excel: Master Power Query in 120 Minutes!, this bundle covers a wide range of topics to help you master Excel's advanced functions.</p><p>With our Microsoft Excel Advanced at QLS Level 7 bundle, you'll have the skills and knowledge to confidently tackle any Excel challenge and impress your colleagues and employers. Don't miss out on this opportunity to take your career to new heights - enrol in our exclusive bundle today!</p><p><strong>Learning Outcomes:</strong></p><p>By completing the Microsoft Excel Advanced at QLS Level 7 bundle, you will be able to:</p><ul><li>Master essential Excel formulas and functions to improve data analysis and reporting.</li><li>Utilise Excel's advanced data tools to manage and manipulate large datasets with ease.</li><li>Use Excel's powerful analysis tools to identify patterns, trends and insights within data.</li><li>Create dynamic and professional Gantt charts and timelines to visualise project progress.</li><li>Harness the power of Excel's lookup functions to retrieve data and information quickly.</li><li>Use Power Query to clean, transform and load data from multiple sources.</li><li>Become proficient in using Microsoft Excel at an advanced level.</li></ul><p><strong>QLS Endorsed Courses: </strong></p><ul><li><strong>Course 01: </strong>Diploma in Excel 2016 Formulas and Functions at QLS Level 4</li><li><strong>Course 02: </strong>Excel Data Tools and Data Management</li></ul><p><strong>CPD QS Accredited Courses:</strong></p><ul><li><strong>Course 03: </strong>Microsoft Excel Course</li><li><strong>Course 04: </strong>Excel Data Analysis</li><li><strong>Course 05:</strong> Excel Vlookup, Xlookup, Match and Index</li><li><strong>Course 06: </strong>Dynamic Excel Gantt Chart and Timelines</li><li><strong>Course 07: </strong>Microsoft Excel: Master Power Query in 120 Minutes!</li></ul><p>The Microsoft Excel Advanced at QLS Level 7 bundle is designed to help you master advanced Excel skills and techniques. The bundle includes two QLS-endorsed courses and five relevant CPD QS-accredited courses, covering a wide range of Excel functions and features.</p><p>The QLS-endorsed courses provide hardcopy certificates upon completion, while the CPD QS-accredited courses offer practical knowledge and insights to immediately apply to your work. With this exclusive bundle, you'll gain the skills and confidence to tackle any Excel challenge and take your career to new heights.</p><p><strong>Certification</strong></p><p>Learners will qualify for the <strong>highly sought-after QLS Endorsed Certificate</strong> after successfully passing the assessment at the conclusion of each endorsed course.</p><p><strong>The Quality Licence Scheme</strong> is a credible and renowned endorsement that marks <strong>high quality </strong><strong>and excellence</strong> in the UK. It is well accepted and sought after by industry experts and recruiters.</p><p>Learners who purchase this bundle will receive <strong>TWO Hardcopy QLS Certificates at their door!</strong></p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        15 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This course is suitable for anyone who wants to enhance their Excel skills and take their career to the next level. Specifically, this course is ideal for:</p><ul><li>Business professionals who regularly use Excel for data analysis and reporting.</li><li>Accounting and finance professionals who use Excel for budgeting and financial analysis.</li><li>Project managers who need to create dynamic and professional Gantt charts and timelines.</li><li>Anyone who wants to improve their Excel skills and knowledge.</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Completing the Microsoft Excel Advanced at QLS Level 7 bundle can lead to a wide range of career opportunities, including:</p><ul><li>Business Analyst (£25,000 - £55,000)</li><li>Financial Analyst (£26,000 - £60,000)</li><li>Data Analyst (£24,000 - £47,000)</li><li>Project Manager (£29,000 - £64,000)</li><li>Management Accountant (£25,000 - £55,000)</li><li>Business Intelligence Analyst (£24,000 - £61,000)</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

One Education

Microsoft Excel Advanced at QLS  Level 7 Course

General Admission

Imperial Academy

Data Science

Microsoft Excel

Tableau

Python

Data Science: Basics, Data Mining, Excel, Python, SQL, Machine Learning & Tableau

<strong>In this course, you will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries and perform exploratory data analysis (EDA) by visualizing a data set using a variety of charts.</strong>
        <p>In the first and second course of the 'Machine Learning for Absolute Beginners' training program, you have learned the fundamentals of AI and machine learning and discovered methods to pre-process the data before moving it into the machine learning algorithms. In this third and final course of the program, you will learn how to create eye-catching data visualizations using Python, Seaborn, and Matplotlib.

The course starts by highlighting the learning objectives and then takes you through the fundamentals of Matplotlib and Seaborn. You will learn how to use figures, axes, customization techniques, and NumPy to perform data visualization. In the rest of this course, you will discover how to develop the ranking, proportion, trend, distribution, and correlation charts.

By the end of this course, you will have the knowledge and skills to perform data visualization and exploratory data analysis (EDA) using Python, Matplotlib, and Seaborn.

The code files and all related files are placed on GitHub at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-3</p>
        <h2>What You Will Learn</h2><p>Become familiar with object-oriented and Pyplot interfaces of Matplotlib<br>Understand Seaborn and figure-level and axes-level functions<br>Find out how to create pie, treemap, and swarm charts<br>Plot histogram, density, box, and whisker charts<br>Create bar, grouped bar, stacked bar, and lollipop charts<br>Create scatter, correlogram, line, and area charts</p>
        <h2>Audience</h2><p>This course is designed for absolute beginners who want to learn how to visualize and create appealing charts using Python, Matplotlib, and Seaborn. Basic Python skills and good knowledge of the Pandas library is needed to get started with this course. Hence, it is recommended to complete Level 1 and Level 2 of the "Machine Learning for Absolute Beginners" training program before taking up this course.</p>
        <h2>Approach</h2><p>With the help of exercises and activities, this course will show you how to use Python, Matplotlib, and Seaborn for data visualization and exploratory data analysis (EDA).</p>
        <h2>Key Features</h2><p>Grasp the fundamentals of Matplotlib and Seaborn * Become confident in performing exploratory data analysis (EDA) for any data sets * Get ready to visualize data using a variety of charts</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-3</p>
        <h2>About the Author</h2><h3>Idan Gabrieli</h3><p>Idan Gabrieli has worked in various engineering positions in Israel's high-tech industry. Idan has gained extensive experience with hundreds of business companies, transforming their challenges and opportunities into practical use cases and leveraging cutting-edge technologies.

Idan's expertise spans multiple domains, including cloud computing, machine learning, data science, and electronics. Since 2014, Idan has created and published online courses on various topics worldwide. Idan is recognized as a high-rated instructor by leading educational providers.

Idan simplifies complex technology and provides high-quality educational content with specific learning objectives that are well-structured, combining various multimedia teaching options.</p>
        <h2>Course Outline</h2><h4>1. Getting Started with Level 3!</h4><p></p><br><h4>2. Data Visualization with Matplotlib and Seaborn</h4><p></p><br><h4>3. Ranking and Proportion Charts</h4><p></p><br><h4>4. Trend and Distribution Charts</h4><p></p><br><h4>5. Correlation Charts</h4><p></p><br><h4>6. Course Summary</h4><p></p>

Packt

Data Visualization

In this course, you will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries and perform exploratory data analysis (EDA) by visualizing a data set using a variety of charts.

Machine Learning for Absolute Beginners - Level 3

London

<h2>Lean Six Sigma Black Belt Certification Program: In-House Training</h2>
 <p>This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners.</p>
 <p>If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others.</p>
 <p>Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course.</p><h3>What you Will Learn</h3> 
 <p>At the end of this program, you will be able to:</p> 
 <ul> 
 <li>Use Minitab for advanced data analysis</li> 
 <li>Develop appropriate sampling strategies</li> 
 <li>Analyze differences between samples using Hypothesis Tests</li> 
 <li>Apply Statistical Process Control to differentiate common cause and special cause variation</li> 
 <li>Explain and apply various process capability metrics</li> 
 <li>Conduct Measurement System Analysis and Gage R&amp;R studies for both discrete and continuous data</li> 
 <li>Conduct and analyze simple and multiple regression analysis</li> 
 <li>Plan, execute, and analyze designed experiments</li> 
 <li>Drive sustainable change efforts through leadership, change management, and stakeholder management</li> 
 <li>Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps</li> 
 <li>Explain the main concepts of Design for Six Sigma including QFD</li> 
 </ul><section>
                    <h3>Introduction: DMAIC Review</h3> <ul>  <li>IIL Black Belt Certification Requirements</li>  <li>Review Project Selection</li>  <li>Review Define</li>  <li>Review Measure</li>  <li>Review Analyze</li>  <li>Review Improve</li>  <li>Review Control</li>  </ul>  <h3>Introduction: Minitab Tool</h3> <ul>  <li>Introduction to Minitab</li>  <li>Minitab basic statistics and graphs</li>  <li>Special features</li>  <li>Overview of Minitab menus</li>  </ul>  <h3>Introduction: Sampling</h3> <ul>  <li>The Central Limit Theorem</li>  <li>Confidence Interval of the mean</li>  <li>Sample size for continuous data (mean)</li>  <li>Confidence Interval for proportions</li>  <li>Sample size for discrete data (proportions)</li>  <li>Sampling strategies (review)</li>  <li>Appendix: CI and sample size for confidence levels other than 95%</li>  </ul>  <h3>Hypothesis Testing: Introduction</h3> <ul>  <li>Why use advanced stat tools?</li>  <li>What are hypothesis tests?</li>  <li>The seven steps of hypothesis tests</li>  <li>P value errors and hypothesis tests</li>  </ul>  <h3>Hypothesis Testing: Tests for Averages</h3> <ul>  <li>1 factor ANOVA and ANOM</li>  <li>Main Effect Plots, Interaction Plots, and Multi-Vari Charts</li>  <li>2 factor ANOVA and ANOM</li>  </ul>  <h3>Hypothesis Testing: Tests for Standard Deviations</h3> <ul>  <li>Testing for equal variance</li>  <li>Testing for normality</li>  <li>Choosing the right hypothesis test</li>  </ul>  <h3>Hypothesis Testing: Chi Square and Other Hypothesis Test</h3> <ul>  <li>Chi-square test for 1 factor</li>  <li>ANOM test for 1 factor</li>  <li>Chi-square test for 2 factors</li>  <li>Exercise hypothesis tests - shipping</li>  <li>Non-parametric tests</li>  </ul>  <h3>Analysis: Advanced Control Charts</h3> <ul>  <li>Review of Common Cause and Special Cause Variation</li>  <li>Review of the Individuals Control Charts</li>  <li>How to calculate Control Limits</li>  <li>Four additional tests for Special Causes</li>  <li>Control Limits after Process Change</li>  <li>Discrete Data Control Charts</li>  <li>Control Charts for Discrete Proportion Data</li>  <li>Control Charts for Discrete Count Data</li>  <li>Control Charts for High Volume Processes with Continuous Data</li>  </ul>  <h3>Analysis: Non-Normal Data</h3> <ul>  <li>Test for normal distribution</li>  <li>Box-Cox Transformation</li>  <li>Box-Cox Transformation for Individuals Control Charts</li>  </ul>  <h3>Analysis: Time Series Analysis</h3> <ul>  <li>Introduction to Time Series Analysis</li>  <li>Decomposition</li>  <li>Smoothing: Moving Average</li>  <li>Smoothing: EWMA</li>  </ul>  <h3>Analysis: Process Capability</h3> <ul>  <li>Process capability</li>  <li>Discrete Data: Defect metrics</li>  <li>Discrete Data: Yield metrics</li>  <li>Process Capability for Continuous Data: Sigma Value</li>  <li>Short- and long-term capabilities</li>  <li>Cp, Cpk, Pp, Ppk capability indices</li>  </ul>  <h3>Analysis: Measurement System Analysis</h3> <ul>  <li>What is Measurement System Analysis?</li>  <li>What defines a good measurement system?</li>  <li>Gage R&amp;R Studies</li>  <li>Attribute / Discrete Gage R&amp;R</li>  <li>Continuous Gage R&amp;R</li>  </ul>  <h3>Regression Analysis: Simple Correlation</h3> <ul>  <li>Correlation Coefficient</li>  <li>Simple linear regression</li>  <li>Checking the fit of the Regression Model</li>  <li>Leverage and influence analysis</li>  <li>Correlation and regression pitfalls</li>  </ul>  <h3>Regression Analysis: Multiple Regression Analysis</h3> <ul>  <li>Introduction to Multiple Regression</li>  <li>Multicollinearity</li>  <li>Multiple Regression vs. Simple Linear Regression</li>  </ul>  <h3>Regression Analysis: Multiple Regression Analysis with Discrete Xs</h3> <ul>  <li>Introduction</li>  <li>Creating indicator variables</li>  <li>Method 1: Going straight to the intercepts</li>  <li>Method 2: Testing for differences in intercepts</li>  </ul>  <h3>Logistic Regression: Logistic Regression</h3> <ul>  <li>Introduction to Logistic Regression</li>  <li>Logistic Regression - Adding a Discrete X</li>  </ul>  <h3>Design of Experiments: Introduction</h3> <ul>  <li>Design of Experiment</li>  <li>OFAT experimentation</li>  <li>Full factorial design</li>  <li>Fractional factorial design</li>  <li>DOE road map, hints, and suggestions</li>  </ul>  <h3>Design of Experiments: Full Factorial Designs</h3> <ul>  <li>Creating 2k Full Factorial designs in Minitab</li>  <li>Randomization</li>  <li>Replicates and repetitions</li>  <li>Analysis of results: Factorial plots</li>  <li>Analysis of results: Factorial design</li>  <li>Analysis of results: Fits and Residuals</li>  <li>Analysis of results: Response Optimizer</li>  <li>Analysis of results: Review</li>  </ul>  <h3>Design of Experiments: Pragmatic Approaches</h3> <ul>  <li>Designs with no replication</li>  <li>Fractional factorial designs</li>  <li>Screening Design of Experiment Case Study Repair Time</li>  <li>Blocking</li>  </ul>  <h3>Closing: Organizational Change Management</h3> <ul>  <li>Organizational change management</li>  <li>Assuring project sponsorship</li>  <li>Emphasizing shared need for change</li>  <li>Mobilizing stakeholder commitment</li>  </ul>  <h3>Closing: Project Management for Lean Six Sigma</h3> <ul>  <li>Introduction to project management</li>  <li>Project management for Lean Six Sigma</li>  <li>The project baseline plan</li>  <li>Work Breakdown Structure (WBS)</li>  <li>Resource planning</li>  <li>Project budget</li>  <li>Project risk</li>  <li>Project schedule</li>  <li>Project executing</li>  <li>Project monitoring and controlling and Closing</li>  </ul>  <h3>Closing: Design for Lean Six Sigma</h3> <ul>  <li>Introduction to Design for Lean Six Sigma (DMADV)</li>  <li>Introduction to Quality Function Deployment (QFD)</li>  </ul>  <h3>Summary and Next Steps</h3> <ul>  <li>IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)</li>  </ul>


                </section>

IIL Europe Ltd

Lean Six Sigma Black Belt Certification Program: In-House Training

<h2>Lean Six Sigma Black Belt Certification Program</h2> 
 <p>This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners.</p> 
 <p>If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others.</p> 
 <p>Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course.</p><h3>What you Will Learn</h3> 
 <p>At the end of this program, you will be able to:</p> 
 <ul> 
 <li>Use Minitab for advanced data analysis</li> 
 <li>Develop appropriate sampling strategies</li> 
 <li>Analyze differences between samples using Hypothesis Tests</li> 
 <li>Apply Statistical Process Control to differentiate common cause and special cause variation</li> 
 <li>Explain and apply various process capability metrics</li> 
 <li>Conduct Measurement System Analysis and Gage R&amp;R studies for both discrete and continuous data</li> 
 <li>Conduct and analyze simple and multiple regression analysis</li> 
 <li>Plan, execute, and analyze designed experiments</li> 
 <li>Drive sustainable change efforts through leadership, change management, and stakeholder management</li> 
 <li>Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps</li> 
 <li>Explain the main concepts of Design for Six Sigma including QFD</li> 
 </ul><section>
                    <h3>Introduction: DMAIC Review</h3> <ul>  <li>IIL Black Belt Certification Requirements</li>  <li>Review Project Selection</li>  <li>Review Define</li>  <li>Review Measure</li>  <li>Review Analyze</li>  <li>Review Improve</li>  <li>Review Control</li>  </ul>  <h3>Introduction: Minitab Tool</h3> <ul>  <li>Introduction to Minitab</li>  <li>Minitab basic statistics and graphs</li>  <li>Special features</li>  <li>Overview of Minitab menus</li>  </ul>  <h3>Introduction: Sampling</h3> <ul>  <li>The Central Limit Theorem</li>  <li>Confidence Interval of the mean</li>  <li>Sample size for continuous data (mean)</li>  <li>Confidence Interval for proportions</li>  <li>Sample size for discrete data (proportions)</li>  <li>Sampling strategies (review)</li>  <li>Appendix: CI and sample size for confidence levels other than 95%</li>  </ul>  <h3>Hypothesis Testing: Introduction</h3> <ul>  <li>Why use advanced stat tools?</li>  <li>What are hypothesis tests?</li>  <li>The seven steps of hypothesis tests</li>  <li>P value errors and hypothesis tests</li>  </ul>  <h3>Hypothesis Testing: Tests for Averages</h3> <ul>  <li>1 factor ANOVA and ANOM</li>  <li>Main Effect Plots, Interaction Plots, and Multi-Vari Charts</li>  <li>2 factor ANOVA and ANOM</li>  </ul>  <h3>Hypothesis Testing: Tests for Standard Deviations</h3> <ul>  <li>Testing for equal variance</li>  <li>Testing for normality</li>  <li>Choosing the right hypothesis test</li>  </ul>  <h3>Hypothesis Testing: Chi Square and Other Hypothesis Test</h3> <ul>  <li>Chi-square test for 1 factor</li>  <li>ANOM test for 1 factor</li>  <li>Chi-square test for 2 factors</li>  <li>Exercise hypothesis tests - shipping</li>  <li>Non-parametric tests</li>  </ul>  <h3>Analysis: Advanced Control Charts</h3> <ul>  <li>Review of Common Cause and Special Cause Variation</li>  <li>Review of the Individuals Control Charts</li>  <li>How to calculate Control Limits</li>  <li>Four additional tests for Special Causes</li>  <li>Control Limits after Process Change</li>  <li>Discrete Data Control Charts</li>  <li>Control Charts for Discrete Proportion Data</li>  <li>Control Charts for Discrete Count Data</li>  <li>Control Charts for High Volume Processes with Continuous Data</li>  </ul>  <h3>Analysis: Non-Normal Data</h3> <ul>  <li>Test for normal distribution</li>  <li>Box-Cox Transformation</li>  <li>Box-Cox Transformation for Individuals Control Charts</li>  </ul>  <h3>Analysis: Time Series Analysis</h3> <ul>  <li>Introduction to Time Series Analysis</li>  <li>Decomposition</li>  <li>Smoothing: Moving Average</li>  <li>Smoothing: EWMA</li>  </ul>  <h3>Analysis: Process Capability</h3> <ul>  <li>Process capability</li>  <li>Discrete Data: Defect metrics</li>  <li>Discrete Data: Yield metrics</li>  <li>Process Capability for Continuous Data: Sigma Value</li>  <li>Short- and long-term capabilities</li>  <li>Cp, Cpk, Pp, Ppk capability indices</li>  </ul>  <h3>Analysis: Measurement System Analysis</h3> <ul>  <li>What is Measurement System Analysis?</li>  <li>What defines a good measurement system?</li>  <li>Gage R&amp;R Studies</li>  <li>Attribute / Discrete Gage R&amp;R</li>  <li>Continuous Gage R&amp;R</li>  </ul>  <h3>Regression Analysis: Simple Correlation</h3> <ul>  <li>Correlation Coefficient</li>  <li>Simple linear regression</li>  <li>Checking the fit of the Regression Model</li>  <li>Leverage and influence analysis</li>  <li>Correlation and regression pitfalls</li>  </ul>  <h3>Regression Analysis: Multiple Regression Analysis</h3> <ul>  <li>Introduction to Multiple Regression</li>  <li>Multicollinearity</li>  <li>Multiple Regression vs. Simple Linear Regression</li>  </ul>  <h3>Regression Analysis: Multiple Regression Analysis with Discrete Xs</h3> <ul>  <li>Introduction</li>  <li>Creating indicator variables</li>  <li>Method 1: Going straight to the intercepts</li>  <li>Method 2: Testing for differences in intercepts</li>  </ul>  <h3>Logistic Regression: Logistic Regression</h3> <ul>  <li>Introduction to Logistic Regression</li>  <li>Logistic Regression - Adding a Discrete X</li>  </ul>  <h3>Design of Experiments: Introduction</h3> <ul>  <li>Design of Experiment</li>  <li>OFAT experimentation</li>  <li>Full factorial design</li>  <li>Fractional factorial design</li>  <li>DOE road map, hints, and suggestions</li>  </ul>  <h3>Design of Experiments: Full Factorial Designs</h3> <ul>  <li>Creating 2k Full Factorial designs in Minitab</li>  <li>Randomization</li>  <li>Replicates and repetitions</li>  <li>Analysis of results: Factorial plots</li>  <li>Analysis of results: Factorial design</li>  <li>Analysis of results: Fits and Residuals</li>  <li>Analysis of results: Response Optimizer</li>  <li>Analysis of results: Review</li>  </ul>  <h3>Design of Experiments: Pragmatic Approaches</h3> <ul>  <li>Designs with no replication</li>  <li>Fractional factorial designs</li>  <li>Screening Design of Experiment Case Study Repair Time</li>  <li>Blocking</li>  </ul>  <h3>Closing: Organizational Change Management</h3> <ul>  <li>Organizational change management</li>  <li>Assuring project sponsorship</li>  <li>Emphasizing shared need for change</li>  <li>Mobilizing stakeholder commitment</li>  </ul>  <h3>Closing: Project Management for Lean Six Sigma</h3> <ul>  <li>Introduction to project management</li>  <li>Project management for Lean Six Sigma</li>  <li>The project baseline plan</li>  <li>Work Breakdown Structure (WBS)</li>  <li>Resource planning</li>  <li>Project budget</li>  <li>Project risk</li>  <li>Project schedule</li>  <li>Project executing</li>  <li>Project monitoring and controlling and Closing</li>  </ul>  <h3>Closing: Design for Lean Six Sigma</h3> <ul>  <li>Introduction to Design for Lean Six Sigma (DMADV)</li>  <li>Introduction to Quality Function Deployment (QFD)</li>  </ul>  <h3>Summary and Next Steps</h3> <ul>  <li>IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)</li>  </ul>


                </section>

Lean Six Sigma Black Belt Certification Program

School of Business and Technology London

QUALIFI Level 3 Diploma in Data Science

<p>As the world becomes increasingly data-driven, the demand for skilled data scientists continues to grow at an exponential rate. In the UK alone, the number of data science jobs has increased by over 300% in the past five years, according to recent statistics. This has created a massive opportunity for individuals with the skills and expertise to analyse data, draw insights, and make informed decisions.</p><p>The <strong>Data Scientist-Quality Licence Scheme (QLS) endorsed courses</strong> bundle is designed to help individuals tap into this growing demand by providing a comprehensive set of courses that cover the core skills and knowledge needed to become a data scientist. With<strong> 10 QLS-endorsed certificates included free of charge</strong>, learners can be confident that their learning is backed by a reputable and respected organisation.</p><p>Data science is a rapidly growing field, and individuals who possess the skills and expertise to analyse data and draw insights are in high demand. In fact, recent statistics show that the demand for data scientists in the UK has increased by over 300% in the past five years, with no signs of slowing down. By learning data science, individuals can position themselves for success in a variety of fields, from finance and healthcare to marketing and technology.</p><p>So why wait? Sign up for the Data Scientist-Quality Licence Scheme (QLS) endorsed courses bundle today and take the first step towards a lucrative and rewarding career in data science. With a wide range of courses to choose from and 10 QLS-endorsed certificates included free of charge, there's never been a better time to invest in yourself and your future.</p><p>Sign up for the Data Scientist-Quality Licence Scheme (QLS) endorsed courses bundle today and unlock your full potential.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Gain proficiency in R programming for data science, including data visualisation and statistical analysis.</li><li>Develop a comprehensive understanding of statistical concepts in R, including hypothesis testing and regression analysis.</li><li>Acquire essential knowledge of data science and machine learning with R, including supervised and unsupervised learning algorithms and data analysis techniques.</li><li>Learn the fundamentals of CSS web development and responsive web design.</li><li>Develop mastery in Bootstrap 5 course and responsive web design techniques.</li><li>Gain a foundation in HTML5 web development, including website design and multimedia integration.</li><li>Acquire advanced knowledge of statistics and probability for data science and machine learning.</li></ul><p><strong>Please Note:</strong> Imperial Academy is One Education approved resale partner for Quality Licence Scheme Endorsed courses.</p><p>The Data Scientist-Quality Licence Scheme (QLS) endorsed courses bundle is designed to provide individuals with the skills and knowledge needed to succeed in the field of data science. This bundle includes a range of courses covering topics such as R programming, statistical analysis, machine learning, web development, and more.</p><p>With the R Programming for Data Science course, learners will gain proficiency in R programming, including data visualisation and statistical analysis. The Statistical Concepts in R course offers a comprehensive overview of statistical concepts in R, including hypothesis testing and regression analysis. The 2021 Data Science &amp; Machine Learning with R from A-Z course provides an in-depth understanding of data science and machine learning with R. The CSS Web Development Crash Course offers a foundation in CSS web development, while the Masterclass Bootstrap 5 Course - Responsive Web Design provides an in-depth exploration of Bootstrap 5 course and responsive web design techniques. The Statistics &amp; Probability for Data Science &amp; Machine Learning course offers an advanced exploration of statistics and probability for data science and machine learning.</p><p><strong>This bundle comprises the following courses:</strong></p><p><strong>QLS Endorsed Courses:</strong></p><ul><li><strong>Course 01:</strong> R Programming for Data Science</li><li><strong>Course 02:</strong> Statistical Concepts in R</li><li><strong>Course 03:</strong> 2021 Data Science &amp; Machine Learning with R from A-Z</li><li><strong>Course 04:</strong> CSS Web Development Crash Course</li><li><strong>Course 05:</strong> Masterclass Bootstrap 5 Course - Responsive Web Design</li><li><strong>Course 06:</strong> Basic HTML 5</li><li><strong>Course 07:</strong> Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li><strong>Course 08:</strong> Excel Data Analysis</li><li><strong>Course 09:</strong> Career Coaching</li><li><strong>Course 10:</strong> The Unstoppable Self-Confidence &amp; High Self-Esteem Blueprint</li></ul><p><strong>Certificate: </strong></p><p>The Quality Licence Scheme ensures excellence and quality. These courses' learning outcomes provide the learners with high competence in their line of work as well. So, QLS-endorsed courses deliver not only deep knowledge but also add great value to the resume.</p><p>After completing the assessments, learners will be eligible for a prestigious QLS Certificate for each endorsed course in this bundle. Moreover, the certificates will be delivered to their home free of cost!</p><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Individuals seeking to enter the field of data science or advance their career in this field.</li><li>Programmers looking to expand their skills and knowledge base in data science and machine learning.</li><li>Students pursuing a career in data science, statistics, or related fields.</li><li>Professionals looking to enhance their data analysis skills.</li><li>Anyone with an interest in learning more about data science and machine learning.</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst - £20,000 to £50,000 per year</li><li>Data Scientist - £30,000 to £90,000 per year</li><li>Business Intelligence Analyst - £25,000 to £65,000 per year</li><li>Machine Learning Engineer - £40,000 to £100,000 per year</li><li>Financial Analyst - £25,000 to £65,000 per year</li><li>Statistician - £20,000 to £65,000 per year</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

10 QLS Endorsed Courses for Data Scientist  | 10 Endorsed Certificates Included | Life Time Access

Data Scientist - QLS Endorsed Courses

<strong>With this course, you'll learn how to connect to the data source in Tableau and use Tableau for data visualization. Along the process, you'll get to grips with Tableau dashboards, explore storytelling with Tableau, and perform actions to share data with others.</strong>
        <p>Do you want to help your organization make effective data-driven decisions? You can do that by visualizing the data in a way that everyone in your organization understands the relationship between the data and is able to make smart marketing decisions with ease. This video course will teach you how to create effective data visualizations using Tableau with the help of interesting activities.
The course begins with an introduction to Tableau, showing you how to connect to a data source in Tableau. You'll then gain a solid understanding of data visualization, before going on to develop a bar chart and a pie chart, create a text table and explore map visualization in Tableau. The course will also help you to find a suitable method for using filters in a Tableau worksheet. As you advance, you'll delve into data connections by connecting multiple tables in the same data source. Toward the end, you'll learn how to effectively use the Tableau dashboard, create stories in Tableau, and share your data with others without any hassles.
By the end of this course, you'll have the knowledge you need to create data visualizations using Tableau 10 and Tableau 2019, and be ready to delve further into advanced Tableau topics.</p>
        <h2>What You Will Learn</h2><p>Become familiar with the Tableau 10 and the Tableau 2019 interface<br>Find out how to create bar and pie charts<br>Connect with multiple tables in the same data source as well as different data sources<br>Gain the skills you need to create a dashboard<br>Experience storytelling with Tableau<br>Discover the technique of sharing your data with others</p>
        <h2>Audience</h2><p>If you're a beginner in marketing, or an experienced marketer or a digital analyst who is looking to learn Tableau for data visualization, then this course is for you. Basic computer skills are required to get started with this course.</p>
        <h2>Approach</h2><p>This course takes you through a variety of activities that will enable you to use Tableau 10 and Tableau 2019 effectively for smart data visualization and analysis.</p>
        <h2>Key Features</h2><p>Get acquainted with Tableau for effective data visualization * Learn how to use Tableau's drag and drop and built-in functions optimally * Develop the skills you need to connect Tableau with various data sources</p>
        
        <h2>About the Author</h2><h3>Anil Batra </h3><p>Anil Batra, founder of Global Analytics Academy and Optizent - a digital marketing and analytics consulting company, is a seasoned digital marketing and analytics professional with 15 years of experience. He has worked with companies ranging from Fortune 50 to various start-ups and has helped them improve marketing results. His customers include Microsoft, SmartMoney, ESPN, T-Mobile, Hoovers, RealNetworks, Starbucks, and TheStreet. He has taught and trained several marketing and analytics professionals in the past 9 years of teaching at UBC, University of Washington, and Bellevue College. Anil also teaches digital marketing, digital analytics, Google Analytics, Tableau, and social media courses.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video provides an introduction to the course.</p></td></tr></tbody></table><br><h4>2. Introduction to Tableau</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Getting Started with Tableau - Overview of the Home Screen</p><p style='margin: 0'>This video provides an overview of the Tableau home screen.</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Connections and Data Manipulation</p><p style='margin: 0'>This video explains the concept of data connections and data manipulation in Tableau.</p></td></tr><tr><td style='padding: 15px;'><p>3. Overview of the Worksheet Interface</p><p style='margin: 0'>This video provides an overview of the worksheet interface.</p></td></tr></tbody></table><br><h4>3. Creating Visualization</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Developing Bar Chart and Adding Colors, Details, and Labels Using Marks Card</p><p style='margin: 0'>This video explains how to create a Bar chart and add colors, details, and labels using the Marks card option.</p></td></tr><tr><td style='padding: 15px;'><p>2. Bar Chart - Vertical and Horizontal and Switching Between Them</p><p style='margin: 0'>This video explains how to create vertical and horizontal Bar charts and how to switch between them.</p></td></tr><tr><td style='padding: 15px;'><p>3. Plotting Multiple Measures -Trends on the Shared Axis and Dual Axis</p><p style='margin: 0'>This video explains how to plot multiple measures on the shared axis and dual axis.</p></td></tr><tr><td style='padding: 15px;'><p>4. Creating a Pie Chart in Tableau</p><p style='margin: 0'>This video explains how to create a Pie chart in Tableau.</p></td></tr><tr><td style='padding: 15px;'><p>5. Creating a Text Table in Tableau</p><p style='margin: 0'>This video explains how to create a text table in Tableau.</p></td></tr><tr><td style='padding: 15px;'><p>6. Creating a Map Visualization in Tableau</p><p style='margin: 0'>This video explains how to create a map visualization in Tableau.</p></td></tr><tr><td style='padding: 15px;'><p>7. Using Filters in Tableau Worksheets</p><p style='margin: 0'>This video demonstrates how to use filters in Tableau worksheets.</p></td></tr></tbody></table><br><h4>4. More about Data Collections</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Connecting to Multiple Tables in the Same Data Source</p><p style='margin: 0'>This video explains how to connect multiple tables in the same data source.</p></td></tr></tbody></table><br><h4>5. Dashboards and Stories</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Creating a Tableau Dashboard</p><p style='margin: 0'>This video explains how to create a Tableau dashboard.</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a Story in Tableau</p><p style='margin: 0'>This video explains how to create a story in Tableau.</p></td></tr></tbody></table>

Digital Marketing

Data Analysis

With this course, you'll learn how to connect to the data source in Tableau and use Tableau for data visualization. Along the process, you'll get to grips with Tableau dashboards, explore storytelling with Tableau, and perform actions to share data with others.

Tableau Desktop - A Step-by-Step Guide for Beginners

<p><strong>24 Hour Flash Deal **25-in-1 </strong><strong>Chief Data Officer (CDO) Advanced Diploma </strong><strong>Mega Bundle**</strong></p><p><strong> </strong><strong>Chief Data Officer (CDO) Advanced Diploma </strong><strong>Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong></p><p>Take the initial steps toward a successful long-term career by studying the <strong>Chief Data Officer (CDO) Advanced Diploma</strong> package online with <strong>Studyhub </strong>through our online learning platform. The Chief Data Officer (CDO) Advanced Diploma bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.</p><p>This <strong>Chief Data Officer (CDO) Advanced Diploma </strong>course provides complete 360-degree training on Chief Data Officer (CDO) Advanced Diploma. You'll get not one, not two, not three, but <strong>twenty-five </strong>Chief Data Officer (CDO) Advanced Diploma courses included in this course. Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these Chief Data Officer (CDO) Advanced Diploma courses are yours for as long as you want them once you enrol in this course</p><p><strong>This Chief Data Officer (CDO) Advanced Diploma Bundle consists the following career oriented courses:</strong></p><ul><li>Outcome</li><li>Course 01: Data Analytics</li><li>Course 02: Basic Data Analysis</li><li>Course 03: Data Analysis in Excel</li><li>Course 04: Data Analysis &amp; Forecasting</li><li>Course 05: Data Analysis, Automating and Visualisation in Excel</li><li>Course 06: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 07: Microsoft Excel Complete Course 2019</li><li>Course 08: VLOOKUP: Master Excel Formula VLOOKUP in 60 minutes!</li><li>Course 09: Excel: Top 50 Microsoft Excel Formulas in 50 Minutes!</li><li>Course 10: Python Basic Programming for Absolute Beginners</li><li>Course 11: Machine Learning Basics</li><li>Course 12: Fundamentals of Business Analysis</li><li>Course 13: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines</li><li>Course 14: PowerBI Formulas</li><li>Course 15: Microsoft Power BI 2021 Complete Course</li><li>Course 16: Data Protection and Data Security (GDPR) Training Certification</li><li>Course 17: Information Governance and Data Management Training</li><li>Course 18: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 19: Data Documentation and Record Keeping Best Practices</li><li>Course 20: Microsoft Access Databases Forms and Reports</li><li>Course 21: SQL Database Management</li><li>Course 22: Data Analytics with Tableau</li><li>Course 23: Business Intelligence and Data Mining</li><li>Course 24: Google Analytics</li><li>Course 25: Quick Data Science Approach from Scratch</li></ul> <p>The <strong>Chief Data Officer (CDO) Advanced Diploma </strong>course has been prepared by focusing largely on Chief Data Officer (CDO) Advanced Diploma career readiness. It has been designed by our Chief Data Officer (CDO) Advanced Diploma specialists in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners.</p><p>The Chief Data Officer (CDO) Advanced Diploma Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Chief Data Officer (CDO) Advanced Diploma bundle course has been created with <strong>twenty-five </strong>premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</p><p>This Chief Data Officer (CDO) Advanced Diploma Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Chief Data Officer (CDO) Advanced Diploma Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The Chief Data Officer (CDO) Advanced Diploma course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc.</p><p><strong>In this exclusive </strong><strong>Chief Data Officer (CDO) Advanced Diploma </strong><strong>bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Chief Data Officer (CDO) Advanced Diploma lessons</li><li>One to one assistance from Chief Data Officer (CDO) Advanced Diplomaprofessionals if you need it</li><li>Innovative exams to test your knowledge after the Chief Data Officer (CDO) Advanced Diplomacourse</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all twenty-five Chief Data Officer (CDO) Advanced Diploma courses</li><li>Digital Certificate, Transcript and student ID are all included in the price</li><li>PDF certificate immediately after passing</li><li>Original copies of your Chief Data Officer (CDO) Advanced Diploma certificate and transcript on the next working day</li><li>Easily learn the Chief Data Officer (CDO) Advanced Diploma skills and knowledge you want from the comfort of your home</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This <strong>Chief Data Officer (CDO) Advanced Diploma </strong>training is suitable for -</p><ul><li>Students</li><li>Recent graduates</li><li>Job Seekers</li><li>Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Chief Data Officer (CDO) Advanced Diploma</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Chief Data Officer (CDO) Advanced Diploma </strong>course, all you need is -</p><ul><li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Chief Data Officer (CDO) Advanced Diploma</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to kickstart your <strong>Chief Data Officer (CDO) Advanced Diploma </strong>career because this course includes various courses as a bonus. This Chief Data Officer (CDO) Advanced Diploma is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Chief Data Officer (CDO) Advanced Diploma career opportunities.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><ul><li>CPD Accredited e-Certificate - Free</li><li>CPD Accredited Hardcopy Certificate - Free</li><li>Enrolment Letter - Free</li><li>Student ID Card - Free</li></ul></div>

                        </div>

Studyhub UK

Finance Cert & Exam Prep

Certified Cryptocurrency Investigator Course (CCI)

Certificate of Completion (CCL)

Diploma for School Business Leaders (DSBM)

Certified in Data Protection (CDP)

ICDL (International Certification of Digital Literacy)

Chief Data Officer (CDO) Advanced Diploma

<strong>Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis</strong>
        <p>In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised and supervised learning in Python, you can give your company a competitive edge and level up in your career. This course will give you a robust grounding in clustering and classification, the main aspects of machine learning.

The course consists of 7 sections that will help you master Python machine learning. You'll begin with an introduction to Python data science and Anaconda, which is a powerful Python-driven framework for data science. Next, you'll delve into Pandas and read data structures, including CSV, Excel, and HTML data. As you advance, you'll perform data cleaning and munging to remove NAs\no data and discover how to handle conditional data, group by attributes, and do much more. You'll also grasp basic concepts of unsupervised learning such as K-means clustering and its implementation on the Iris dataset. The course will take you through the theory of dimension reduction and feature selection for machine learning and help you understand Principal Component Analysis (PCA) using two case studies. You'll get to grips with the linear and non-linear classification of SVM along with Gradient Boosting Machine (GBM) and Naive Bayes Classification. Finally, you'll explore neural networks and discover the powerful H20 framework and for deep learning classification. Additionally, you'll learn about perceptrons and Artificial Neural Networks (ANN) for binary classification.
By the end of this course, you'll be able to use packages such as NumPy, Pandas, and Matplotlib to work with real data in Python.

All code and supporting files for this course are available at 
https://github.com/sanjanapackt/PacktPublishing-Clustering-and-Classification-with-Machine-Learning-in-Python.</p>
        <h2>What You Will Learn</h2><p>Harness the power of Anaconda/iPython for practical data science<br>Read data into the Python environment from different sources<br>Carry out basic data preprocessing and wrangling in Python<br>Implement unsupervised/clustering techniques such as k-means clustering<br>Get to grips with dimensionality reduction techniques and feature selection<br>Implement supervised learning/classification techniques such as random forests<br>Explore neural network- and deep learning-based classification<br></p>
        <h2>Audience</h2><p>If you want to build data science applications in the Python environment, this book is for you. You'll also find this book helpful if you want to learn how to implement unsupervised learning on real data using Python, or if you're a student looking to get started with artificial neural networks and deep learning.</p>
        <h2>Approach</h2><p>This course is full of interesting and illustrative examples and easy-to-understand theory to help you implement a real-world concept in every lecture. It covers hands-on methods to simplify and address even the most difficult concepts in Python using minimal jargon.</p>
        <h2>Key Features</h2><p>Explore the most important Python data science concepts and packages, including Pandas * Master the Anaconda framework and use it to implement clustering and classification models on your data * Get to grips with data science fundamentals and understand which models should be used when * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/clustering-and-classification-with-machine-learning-in-r</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome to Clustering & Classification with Machine Learning in Python</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Welcome to Clustering & Classification with Machine Learning in Python</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Machine Learning?</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: What is Machine Learning?</p></td></tr><tr><td style='padding: 15px;'><p>3. Python Data Science Environment</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Python Data Science Environment</p></td></tr><tr><td style='padding: 15px;'><p>4. For Mac Users</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: For Mac Users</p></td></tr><tr><td style='padding: 15px;'><p>5. IPython in Browser</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: IPython in Browser</p></td></tr><tr><td style='padding: 15px;'><p>6. Python Data Science Packages to Be Used</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Python Data Science Packages to Be Used</p></td></tr></tbody></table><br><h4>2. Read in Data from Different Sources with Pandas</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What are Pandas?</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: What are Pandas?</p></td></tr><tr><td style='padding: 15px;'><p>2. Read in Data from CSV</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Data from CSV</p></td></tr><tr><td style='padding: 15px;'><p>3. Read in Online CSV</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Online CSV</p></td></tr><tr><td style='padding: 15px;'><p>4. Read in Excel Data</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Excel Data</p></td></tr><tr><td style='padding: 15px;'><p>5. Read in HTML Data</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in HTML Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Read in Data from Databases</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Data from Databases</p></td></tr></tbody></table><br><h4>3. Data Cleaning & Munging</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Remove Missing Values</p><p style='margin: 0'>Data Cleaning & Munging: Remove Missing Values</p></td></tr><tr><td style='padding: 15px;'><p>2. Conditional Data Selection</p><p style='margin: 0'>Data Cleaning & Munging: Conditional Data Selection</p></td></tr><tr><td style='padding: 15px;'><p>3. Data Grouping</p><p style='margin: 0'>Data Cleaning & Munging: Data Grouping</p></td></tr><tr><td style='padding: 15px;'><p>4. Data Sub setting</p><p style='margin: 0'>Data Cleaning & Munging: Data sub setting</p></td></tr><tr><td style='padding: 15px;'><p>5. Ranking & Sorting</p><p style='margin: 0'>Data Cleaning & Munging: Ranking & Sorting</p></td></tr><tr><td style='padding: 15px;'><p>6. Concatenate</p><p style='margin: 0'>Data Cleaning & Munging: Concatenate</p></td></tr><tr><td style='padding: 15px;'><p>7. Merging & Joining Data Frames</p><p style='margin: 0'>Data Cleaning & Munging: Merging & Joining Data Frames</p></td></tr></tbody></table><br><h4>4. Unsupervised Learning in Python</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Unsupervised Classification- Some Basic Concepts</p><p style='margin: 0'>Unsupervised Learning in Python: Unsupervised Classification- Some Basic Concepts</p></td></tr><tr><td style='padding: 15px;'><p>2. K-Means Clustering: Theory</p><p style='margin: 0'>Unsupervised Learning in Python: K-Means Clustering: Theory</p></td></tr><tr><td style='padding: 15px;'><p>3. Implement K-Means on the Iris Data</p><p style='margin: 0'>Unsupervised Learning in Python: Implement K-Means on the Iris Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Quantifying K-Means Clustering Performance</p><p style='margin: 0'>Unsupervised Learning in Python: Quantifying K-Means Clustering Performance</p></td></tr><tr><td style='padding: 15px;'><p>5. K-Means Clustering with Real Data</p><p style='margin: 0'>Unsupervised Learning in Python: K-Means Clustering with Real Data</p></td></tr><tr><td style='padding: 15px;'><p>6. How to Select the Optimal Number of Clusters?</p><p style='margin: 0'>Unsupervised Learning in Python: How to Select the Optimal Number of Clusters?</p></td></tr><tr><td style='padding: 15px;'><p>7. Gaussian Mixture Modelling (GMM)</p><p style='margin: 0'>Unsupervised Learning in Python: Gaussian Mixture Modelling (GMM)</p></td></tr><tr><td style='padding: 15px;'><p>8. Hierarchical Clustering-theory</p><p style='margin: 0'>Unsupervised Learning in Python: Hierarchical Clustering-theory</p></td></tr><tr><td style='padding: 15px;'><p>9. Hierarchical Clustering-practical</p><p style='margin: 0'>Unsupervised Learning in Python: Hierarchical Clustering-practical</p></td></tr></tbody></table><br><h4>5. Dimension Reduction & Feature Selection for Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Principal Component Analysis (PCA)-Theory</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Theory</p></td></tr><tr><td style='padding: 15px;'><p>2. Principal Component Analysis (PCA)-Case Study 1</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Case Study 1</p></td></tr><tr><td style='padding: 15px;'><p>3. Principal Component Analysis (PCA)-Case Study 2</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Case Study 2</p></td></tr><tr><td style='padding: 15px;'><p>4. Linear Discriminant Analysis (LDA) for Dimension Reduction</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Linear Discriminant Analysis (LDA) for Dimension Reduction</p></td></tr><tr><td style='padding: 15px;'><p>5. t-SNE Dimension Reduction</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: t-SNE Dimension Reduction</p></td></tr><tr><td style='padding: 15px;'><p>6. Feature Selection to Select the Most Relevant Predictors</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Feature Selection to Select the Most Relevant Predictors</p></td></tr><tr><td style='padding: 15px;'><p>7. Recursive Feature Elimination (RFE)</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Recursive Feature Elimination (RFE)</p></td></tr></tbody></table><br><h4>6. Supervised Learning: Classification</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Concepts Behind Supervised Learning</p><p style='margin: 0'>Supervised Learning: Classification: Concepts Behind Supervised Learning</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Preparation for Supervised Learning</p><p style='margin: 0'>Supervised Learning: Classification: Data Preparation for Supervised Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Pointers on Evaluating the Accuracy of Classification Modelling</p><p style='margin: 0'>Supervised Learning: Classification: Pointers on Evaluating the Accuracy of Classification Modelling</p></td></tr><tr><td style='padding: 15px;'><p>4. Using Logistic Regression as a Classification Model</p><p style='margin: 0'>Supervised Learning: Classification: Using Logistic Regression as a Classification Model</p></td></tr><tr><td style='padding: 15px;'><p>5. kNN- Classification</p><p style='margin: 0'>Supervised Learning: Classification: kNN- Classification</p></td></tr><tr><td style='padding: 15px;'><p>6. Naive Bayes Classification</p><p style='margin: 0'>Supervised Learning: Classification: Naive Bayes Classification</p></td></tr><tr><td style='padding: 15px;'><p>7. Linear Discriminant Analysis</p><p style='margin: 0'>Supervised Learning: Classification: Linear Discriminant Analysis</p></td></tr><tr><td style='padding: 15px;'><p>8. SVM- Linear Classification</p><p style='margin: 0'>Supervised Learning: Classification: SVM- Linear Classification</p></td></tr><tr><td style='padding: 15px;'><p>9. Non-Linear SVM Classification</p><p style='margin: 0'>Supervised Learning: Classification: Non-Linear SVM Classification</p></td></tr><tr><td style='padding: 15px;'><p>10. RF-Classification</p><p style='margin: 0'>Supervised Learning: Classification: RF-Classification</p></td></tr><tr><td style='padding: 15px;'><p>11. Gradient Boosting Machine (GBM)</p><p style='margin: 0'>Supervised Learning: Classification: Gradient Boosting Machine (GBM)</p></td></tr><tr><td style='padding: 15px;'><p>12. Voting Classifier</p><p style='margin: 0'>Supervised Learning: Classification: Voting Classifier</p></td></tr></tbody></table><br><h4>7. Neural Networks and Deep Learning Based Classification Techniques</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Perceptrons for Binary Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Perceptrons for Binary Classification</p></td></tr><tr><td style='padding: 15px;'><p>2. Artificial Neural Networks (ANN) for Binary Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Artificial Neural Networks (ANN) for Binary Classification</p></td></tr><tr><td style='padding: 15px;'><p>3. Multi-class Classification With MLP</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Multi-class Classification With MLP</p></td></tr><tr><td style='padding: 15px;'><p>4. Introduction to H20</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Introduction to H20</p></td></tr><tr><td style='padding: 15px;'><p>5. Use H20 for Deep Learning Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Use H20 for Deep Learning Classification</p></td></tr><tr><td style='padding: 15px;'><p>6. H20 Deep Learning for Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: H20 Deep Learning for Classification</p></td></tr></tbody></table>

Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis

Clustering and Classification with Machine Learning in Python

<h2 id="isPasted" fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This advanced financial modelling course will benefit Real Estate Professionals looking to develop their financial modelling skills to the next level. This course is intended to the most ambitious modellers in the property industry who would like to be fully proficient in building complex real estate models.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></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;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">On this course you will...</strong></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" fr-original-style="" style="box-sizing: border-box;">Understand how the application and use of Structured Finance products in Real Estate</li><li value="2" fr-original-style="" style="box-sizing: border-box;">Learn how to introduce several tranches of debt in a development project</li><li value="3" fr-original-style="" style="box-sizing: border-box;">Understand how to model different parties to a project</li><li value="4" fr-original-style="" style="box-sizing: border-box;">Create Joint Venture structures between Developers, Lenders and Equity Partners</li><li value="5" fr-original-style="" style="box-sizing: border-box;">Learn advanced modelling techniques to analyse underlying asset risk</li><li value="6" fr-original-style="" style="box-sizing: border-box;">Understand how underlying asset risk impacts return to all parties to a project</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></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;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who will benefit from this course?</strong></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" fr-original-style="" style="box-sizing: border-box;">Real Estate professionals from a mid to senior level with exposure to Real Estate financial models</li><li value="2" fr-original-style="" style="box-sizing: border-box;">Mid-level to senior Real Estate Analysts who would like to advance their financial modelling skills in areas such as development, portfolio analysis, and risk analysis</li><li value="3" fr-original-style="" style="box-sizing: border-box;">Real Estate Investors who would like to expand their knowledge and understanding of Real Estate cash flow models to an advanced level</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></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;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline</strong></strong>:</p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" fr-original-style="" style="box-sizing: border-box;">Mezzanine debt modelling</li><li value="2" fr-original-style="" style="box-sizing: border-box;">Joint Venture structures between developers and lender/equity partners</li><li value="3" fr-original-style="" style="box-sizing: border-box;">Promote and profit share structure calculations</li><li value="4" fr-original-style="" style="box-sizing: border-box;">Advanced project cash flows with mezzanine debts</li><li value="5" fr-original-style="" style="box-sizing: border-box;">Key Real Estate and investment risks, risk adjustment of exit yields</li><li value="6" fr-original-style="" style="box-sizing: border-box;">Sensitivity and Scenario Analysis</li><li value="7" fr-original-style="" style="box-sizing: border-box;">Monte Carlo Analysis</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></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;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Included in the Course</strong></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" fr-original-style="" style="box-sizing: border-box;">CPD Accredited Certificate &amp; LinkedIn Proficiency Badge</li><li value="2" id="isPasted" fr-original-style="" style="box-sizing: border-box;">Course Manual - In-Person Course attendees will receive a Physical Copy, Virtual Course attendees will receive a Virtual Copy and have the option to purchase a Hard Copy at an additional fee</li><li value="3" fr-original-style="" style="box-sizing: border-box;">Course Files</li><li value="4" fr-original-style="" style="box-sizing: border-box;">Online Learning Platform access - Further Learning Resources (Reading, Files and Videos)</li><li value="5" fr-original-style="" style="box-sizing: border-box;">Post Course Support - Two Months of Questions &amp; Answers, and One year of support is available for an additional fee</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For more information about the Real Estate Modelling Masterclass such as course delivery methods, pricing and dates, please contact Sam on the Bayfield Training Sales team:</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">E - s.musgrave@bayfieldtraining.com</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">T - 01223 517851</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">W - <a href="https://www.bayfieldtraining.com/" target="_blank" rel="nofollow noopener noreferrer ugc" title="https://www.bayfieldtraining.com/" data-airgap-id="125" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">www.bayfieldtraining.com</a></p>



This advanced financial modelling course will benefit Real Estate Professionals looking to develop their financial modelling skills to the next level. This course is intended to the most ambitious modellers in the property industry who would like to be fully proficient in building complex real estate models.


On this course you will...
Understand how the application and use of Structured Finance products in Real Estate
Learn how to introduce several tranches of debt in a development project
Understand how to model different parties to a project
Create Joint Venture structures between Developers, Lenders and Equity Partners
Learn advanced modelling techniques to analyse underlying asset risk
Understand how underlying asset risk impacts return to all parties to a project


Who will benefit from this course?
Real Estate professionals from a mid to senior level with exposure to Real Estate financial models
Mid-level to senior Real Estate Analysts who would like to advance their financial modelling skills in areas such as development, portfolio analysis, and risk analysis
Real Estate Investors who would like to expand their knowledge and understanding of Real Estate cash flow models to an advanced level


Course Outline:
Mezzanine debt modelling
Joint Venture structures between developers and lender/equity partners
Promote and profit share structure calculations
Advanced project cash flows with mezzanine debts
Key Real Estate and investment risks, risk adjustment of exit yields
Sensitivity and Scenario Analysis
Monte Carlo Analysis


Included in the Course
CPD Accredited Certificate & LinkedIn Proficiency Badge
Course Manual - In-Person Course attendees will receive a Physical Copy, Virtual Course attendees will receive a Virtual Copy and have the option to purchase a Hard Copy at an additional fee
Course Files
Online Learning Platform access - Further Learning Resources (Reading, Files and Videos)
Post Course Support - Two Months of Questions & Answers, and One year of support is available for an additional fee


For more information about the Real Estate Modelling Masterclass such as course delivery methods, pricing and dates, please contact Sam on the Bayfield Training Sales team:
E - s.musgrave@bayfieldtraining.com
T - 01223 517851
W - www.bayfieldtraining.com

Bayfield Training

Financial Modelling & Analysis

Real Estate Finance

Financial Modelling

Professional Development

Investment Management

Continuous Professional Development (CPD)

This course is intended to the most ambitious modellers in the property industry who would like to be fully proficient in building complex real estate models.

Real Estate Modelling Masterclass (Advanced Cash Flow Modelling)

<p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Real Estate Investments are unique in that they generate both rental income and capital appreciation, making cash flow modelling an essential tool for Real Estate Investors, Lenders, and Analysts.</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">On this course, we will use case studies to enhance the delegates understanding of Real Estate financial appraisals, and help them fully appreciate the theory behind the numbers. We will cover topics such as discounting, compounding, forecasting rental income and expenses, calculating net operating income (NOI), factoring in capital expenditures, modelling debt service, and determining the internal rate of return (IRR).</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">This course will provide you with a solid foundation for understanding and analysing real estate cash flows.</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">On this course you will...</strong></span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Study the financial concepts of compounding, discounting and in-perpetuity</li><li value="2" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Consider the importance of the timing and uncertainty of both fixed and growing income streams</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Contrast different property yield metrics</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Build-up risk premiums for discount rates, discuss the importance of liquidity, transparency and volatility</li><li value="5" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Compare and contrast time and money-weighted measures of return</li><li value="6" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Learn about valuation principles</li><li value="7" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Contrast value and worth</li><li value="8" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Discuss the importance and sourcing of inputs and outputs</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who will benefit from this course?</strong></span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Professional Real Estate Transaction Managers</li><li value="2" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Asset Managers</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Portfolio Managers</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Recent graduates with exposure to real estate financial modelling</li><li value="5" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">New employees with exposure to real estate financial modelling</li><li value="6" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">People working in Argus, Anaplan or any commercial real estate software and would like to understand financial modelling key principles.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline</strong>:</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Morning</strong></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Real Estate Financial Mathematics</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Time Value of Money</li><li value="2" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Net Present Value (NPV)</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Internal Rate of Return (IRR)</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Growth</li><li value="5" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">What Discount Rate?</li><li value="6" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Certainty of a cash flow</li><li value="7" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Liquidity</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Price, Value and Worth</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Comparing Price, Value and Worth</li><li value="2" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Conventional Valuation Methods</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Term and Reversion, Layer Method</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Property Yields and Capitalisation Method</li><li value="5" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Exit calculations across Europe</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></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;">Afternoon</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Discounted Cash Flow Models</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Investment Appraisal Models</li><li value="2" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Cash flow inputs: Rents, Yields, Growth Rates, Target Returns</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Cash-on-Cash and Equity Multiple</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Discount Rates &amp; Exit Cap Rate</li><li value="5" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Operating Assumptions</li><li value="6" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Adding borrowing and analysing geared returns</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Model Interpretation and Analysis</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Sensitivity analysis and scenario analysis</li><li value="2" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Growth and inflation</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Performance measures</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Contemporary issues for analysis (such as the rise in interest rates)</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Quizzes | Q&amp;A</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Included in the Course</strong></span></p><ul fr-original-style="" style="box-sizing: border-box;"><li value="1" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">A Bayfield Training Certificate &amp; 7.5 CPD Hours</li><li value="2" style="font-size: 16px; box-sizing: border-box;" id="isPasted" fr-original-style="font-size: 16px;">Course Manual - In-Person Course attendees will receive a Physical Copy, Virtual Course attendees will receive a Virtual Copy and have the option to purchase a Hard Copy at an additional fee</li><li value="3" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Course Files</li><li value="4" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Online Learning Platform access - Further Learning Resources (Reading, Files and Videos)</li><li value="5" style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;">Post Course Support - Two Months of Questions &amp; Answers, and One year of support is available for an additional fee</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="font-size: 16px; box-sizing: border-box;" fr-original-style="font-size: 16px;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For more information about the Understanding Key Principles of Real Estate Financial Modelling such as course delivery methods, pricing and dates, please contact Sam on the Bayfield Training Sales team:</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">E - s.musgrave@bayfieldtraining.com</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">T - 01223 517851</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">W - <a href="https://www.bayfieldtraining.com/" target="_blank" rel="nofollow noopener noreferrer ugc" title="https://www.bayfieldtraining.com/" data-airgap-id="125" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">www.bayfieldtraining.com</a></p>



Real Estate Investments are unique in that they generate both rental income and capital appreciation, making cash flow modelling an essential tool for Real Estate Investors, Lenders, and Analysts.
On this course, we will use case studies to enhance the delegates understanding of Real Estate financial appraisals, and help them fully appreciate the theory behind the numbers. We will cover topics such as discounting, compounding, forecasting rental income and expenses, calculating net operating income (NOI), factoring in capital expenditures, modelling debt service, and determining the internal rate of return (IRR).
This course will provide you with a solid foundation for understanding and analysing real estate cash flows.


On this course you will...
Study the financial concepts of compounding, discounting and in-perpetuity
Consider the importance of the timing and uncertainty of both fixed and growing income streams
Contrast different property yield metrics
Build-up risk premiums for discount rates, discuss the importance of liquidity, transparency and volatility
Compare and contrast time and money-weighted measures of return
Learn about valuation principles
Contrast value and worth
Discuss the importance and sourcing of inputs and outputs


Who will benefit from this course?
Professional Real Estate Transaction Managers
Asset Managers
Portfolio Managers
Recent graduates with exposure to real estate financial modelling
New employees with exposure to real estate financial modelling
People working in Argus, Anaplan or any commercial real estate software and would like to understand financial modelling key principles.


Course Outline:
Morning
Real Estate Financial Mathematics
Time Value of Money
Net Present Value (NPV)
Internal Rate of Return (IRR)
Growth
What Discount Rate?
Certainty of a cash flow
Liquidity
Price, Value and Worth
Comparing Price, Value and Worth
Conventional Valuation Methods
Term and Reversion, Layer Method
Property Yields and Capitalisation Method
Exit calculations across Europe


Afternoon
Discounted Cash Flow Models
Investment Appraisal Models
Cash flow inputs: Rents, Yields, Growth Rates, Target Returns
Cash-on-Cash and Equity Multiple
Discount Rates & Exit Cap Rate
Operating Assumptions
Adding borrowing and analysing geared returns
Model Interpretation and Analysis
Sensitivity analysis and scenario analysis
Growth and inflation
Performance measures
Contemporary issues for analysis (such as the rise in interest rates)


Quizzes | Q&A


Included in the Course
A Bayfield Training Certificate & 7.5 CPD Hours
Course Manual - In-Person Course attendees will receive a Physical Copy, Virtual Course attendees will receive a Virtual Copy and have the option to purchase a Hard Copy at an additional fee
Course Files
Online Learning Platform access - Further Learning Resources (Reading, Files and Videos)
Post Course Support - Two Months of Questions & Answers, and One year of support is available for an additional fee


For more information about the Understanding Key Principles of Real Estate Financial Modelling such as course delivery methods, pricing and dates, please contact Sam on the Bayfield Training Sales team:
E - s.musgrave@bayfieldtraining.com
T - 01223 517851
W - www.bayfieldtraining.com

Property Investment

Risk Management

Investment

Financial Risk Management

On this course, we will use case studies to enhance the delegates understanding of Real Estate financial appraisals, and help them fully appreciate the theory behind the numbers. 

Understanding Key Principles of Real Estate Modelling (Advanced Theoretical Course)



Bayfield Training and the University of Cambridge Department of Land Economy
This prestigious eight-week online Real Estate course is suitable for modellers new to Real Estate and experienced Real Estate Analysts looking to formalise their skill set. This course will equip you with skills to start building your own financial models and the certificate will give your employers and colleagues reassurance of your expertise.
If you want to enhance your financial modelling skills over an extended period, the Real Estate Financial Modelling Certificate is the course for you.
This online real estate course has been put together exclusively for the Real Estate Financial Modelling certificate, using state of the art digital resources such as animations, video-steps, digital whiteboard and video-interactions as well as the spreadsheets, text based resources and tutor contact you would expect from any of Bayfield Training’s classroom based courses.
 Assessment is in the form of a guided model build exercise and written model appraisal. Participants benefit from an additional months access to the course platform after submission of the assessment.


On this course you will:
Become a competent model builder, building Real Estate Financial Models from scratch
Learn tricks and concepts from financial modelling experts with decades of experience in practice and academia
Learn how to use Real Estate Financial Models to make informed investment decisions
Learn at a consistent pace over 8 weeks allowing you to take the time to fully grasp this important skill
This course is suitable for:
Chartered Surveyors
Asset Managers
Financial Controllers
Financial Analysts
Investment Managers
Property Managers
Real Estate Students/Recent Graduates
Course Outline:
Module 1 - Economic Context
Introduction to Real Estate Asset Modelling and how it relates to and is distinct from Econometric Models.
Introduction to Real Estate Asset Modelling and how it relates to and is distinct from Econometric Models.
Why Real Estate Asset Modelling is important
Understanding the occupier, asset and development markets and the relevant modelling approaches for each
Real Estate Sub-Sector Key Performance Indicators
Introduction to conventional valuations and financial mathematics
Understanding and minimising errors in Financial Models


Module 2 - Cash Flow Fundamentals
Constructing a financial model from first principles.
Understanding all the components of a basic cash flow model
Understand why Corporate Finance Models and Real Estate Models are different
Financial Model Design
Making the link between valuations, income mathematics and discounted cash flows
Internal Rate of Return, Net Present Value,Worth and other metrics
Features and techniques to aid fast model building


Module 3 - Developing the Cash Flow
Adapting financial models for different periodicities and building rent functions for different rent behaviour.
Understanding how leases vary with respect to rent over time: Rent Reviews, Break Clauses, Rent Free Periods, Lease Expiries etc.
Developing the concept of a Rent Function in Excel
Logic mathematics and Logic functions
Projecting rent to adapt to different lease contracts and growth patterns
Alternative solutions to Logic functions
Comparative analysis of lease structures in different jurisdictions and adapting financial models


Module 4 - Real Estate Data
Understanding the different sources of data, constructing basic time series models and recognising basic patterns.
Key Property market indicators
Characteristics and application of key input metrics for Real Estate Appraisals
Understanding the eight components of Real Estate Price Dynamics
Awareness of the different sources of data
Reading and using general property market reports
Constructing basic time series models and recognising basic patterns


Module 5 - Development Appraisals
Constructing a development appraisal from first principles and understanding development return metrics.
Understanding the key components of a development project
Understanding the difference between development and investment appraisals
Residual Appraisals and Profit Calculations
Cost orientated cash flows and phased sales
Cumulative construction cost patterns: incidental, fixed, loaded and S-curve
Development return metrics and Modified IRRs


Module 6 - Multi-let Cash Flows
Constructing an advanced multi-let cash flow model and learn different techniques to build flexible rent functions.
Multi-let and portfolio model design principles
Building complex date functions and date series
The three multi-let rent projection techniques
Perpendicular Rent Functions
Incorporate advanced rent adjustments into the Rent Function
Incorporate sector and period varying rental growth rates
Simplifying OPEX and CAPEX projections
Discounting techniques on complex and volatile cash flows


Module 7 - Project Finance
Constructing a flexible Real Estate Debt Finance model.
Revision of the Mathematics of amortisation and debt finance
Basic senior debt models and geared net cash flow
LTV, IRR and Interest Rate Dynamics
Flexible term, repayment options and deferred interest
Loan covenant tests
Understanding different tranches of debt
Understanding how complex debt structures impact the returns to different parties


Module 8 - Model Interpretation and Risk Analysis
Learn how to read, analyse and report on real estate financial models.
Understand how to read models and develop an investment narrative
Visualise model outputs using graph functions, conditional formatting, dynamic symbols and dashboards
Learn how to use built-in Sensitivity, Scenario Analysis tools and third-party add-ins
Learn how to construct varied project scenarios in a systematic way
Introduction to Monte Carlo Analysis and VBA
Optimising sale dates and other parameters
Create well written, attractive and persuasive reports


Included in the Course
Bayfield Training and University of Cambridge Accredited Certificate & LinkedIn Proficiency Badge
64 CPD Hours
1 Month Post-Course Access to the Digital Platform - 12 Months Post-Course Access to the Platform can be purchased for an additional fee
Course Files
Q&A Webinars and Guest Speaker Webinars
Further Learning Resources (Reading, Files and Videos)
Post Course Support - Two Months of Questions & Answers


2024 Cohort Dates Include:
3rd June to 29th July
5th August to 25th September 2024
30th September to 25th November


For more information, please contact Sam on the Bayfield Training Sales team:
E - s.musgrave@bayfieldtraining.com
T - 01223 517851
W - www.bayfieldtraining.com

University of Cambridge & Bayfield Training - Real Estate Financial Modelling Certificate (Online Self-Study)

<p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);">Are you looking to enter the dynamic world of real estate?</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Our course is designed to equip you with the knowledge and tools you need to communicate effectively with real estate professionals and develop key skills in real estate investment strategy and analytics.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);">At the end of the course, you&#39;ll be able to read and interpret real estate market reports, and have a firm grasp of how iconic buildings, cities, and companies fit into the overall picture of the real estate sector.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">On this course, you will&hellip;</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Become familiar with the players, structure, general terminology and overall needs of Real Estate.</li><li fr-original-style="" style="box-sizing: border-box;">Learn what is Real Estate and why it is different from other asset classes</li><li fr-original-style="" style="box-sizing: border-box;">Get to grips with the overall size and structure of the UK Real Estate Market</li><li fr-original-style="" style="box-sizing: border-box;">Learn and analyse the links between the different parts of the property market</li><li fr-original-style="" style="box-sizing: border-box;">Understand who works in the Real Estate Market, their qualifications and their job descriptions</li><li fr-original-style="" style="box-sizing: border-box;">Recognise how and when to use basic real estate concepts: Rent, Value, Yield, Risk and Return, etc&hellip;</li><li fr-original-style="" style="box-sizing: border-box;">Learn how to read a real estate market report</li><li fr-original-style="" style="box-sizing: border-box;">Understand how current affairs, politics and economics affects Real Estate Investment</li><li fr-original-style="" style="box-sizing: border-box;">Use household names and iconic companies, cities and buildings to help consolidate your appreciation of this exciting sector</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who will benefit from this course:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Graduates or undergraduates studying economics, finance.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals working in Marketing or Accounting teams within Real Estate firms.</li><li fr-original-style="" style="box-sizing: border-box;">APC students.</li><li fr-original-style="" style="box-sizing: border-box;">Anyone interested in Real Estate.</li><li fr-original-style="" style="box-sizing: border-box;">School leavers/A-Level Students looking to gain an understanding of Real Estate.</li><li fr-original-style="" style="box-sizing: border-box;">Non cognate students who wish to transfer into Real Estate/Finance careers.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">Module 1: What is and why buy Real Estate?</em></em></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">The property Market</li><li fr-original-style="" style="box-sizing: border-box;">The Size and Structure of the UK property market</li><li fr-original-style="" style="box-sizing: border-box;">The impact of Real Estate in the Economy</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">Module 2: The Real Estate Market System</em></em></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">The Space Market</li><li fr-original-style="" style="box-sizing: border-box;">The Asset Market</li><li fr-original-style="" style="box-sizing: border-box;">The Development Market</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">Module 3: How to value Real Estate</em></em></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">An Introduction to Financial Mathematics</li><li fr-original-style="" style="box-sizing: border-box;">The difference between Price, Value and Worth</li><li fr-original-style="" style="box-sizing: border-box;">Property Yield</li><li fr-original-style="" style="box-sizing: border-box;">Conventional Valuation Methods</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">Module 4: How to read a Real Estate Market Report</em></em></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Property Market Indicators: Stock Indicators</li><li fr-original-style="" style="box-sizing: border-box;">Property Market Indicators: Investment Indicators</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">Module 5: Who works in Real Estate?</em></em></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">The build Environment by Cobalt Recruitment</li><li fr-original-style="" style="box-sizing: border-box;">Rea; Estate Agents</li><li fr-original-style="" style="box-sizing: border-box;">Examples of Real Estate Market Agents CVs</li><li fr-original-style="" style="box-sizing: border-box;">Real Estate Network</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Included in the Course</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">CPD Accredited Certificate</li><li fr-original-style="" style="box-sizing: border-box;">12 Months Access to the Course</li><li fr-original-style="" style="box-sizing: border-box;">Course Files</li><li fr-original-style="" style="box-sizing: border-box;">Online Learning Platform access - Further Learning Resources (Reading, Files and Videos)</li><li fr-original-style="" style="box-sizing: border-box;">Post Course Support - Two Months of Questions &amp; Answers, and One year of support is available for an additional fee</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For more information about the Introduction to Real Estate, please contact Sam on the Bayfield Training Sales team:</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">E - s.musgrave@bayfieldtraining.com</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">T - 01223 517851</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">W - <a href="https://www.bayfieldtraining.com/" target="_blank" rel="nofollow noopener noreferrer ugc" title="https://www.bayfieldtraining.com/" data-airgap-id="125" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">www.bayfieldtraining.com</a></p>

Financial Analysis

Are you looking to enter the dynamic world of real estate?

Our course is designed to equip you with the knowledge and tools you need to communicate effectively with real estate professionals and develop key skills in real estate investment strategy and analytics.

At the end of the course, you'll be able to read and interpret real estate market reports, and have a firm grasp of how iconic buildings, cities, and companies fit into the overall picture of the real estate sector.



On this course, you will…

Become familiar with the players, structure, general terminology and overall needs of Real Estate.
Learn what is Real Estate and why it is different from other asset classes
Get to grips with the overall size and structure of the UK Real Estate Market
Learn and analyse the links between the different parts of the property market
Understand who works in the Real Estate Market, their qualifications and their job descriptions
Recognise how and when to use basic real estate concepts: Rent, Value, Yield, Risk and Return, etc…
Learn how to read a real estate market report
Understand how current affairs, politics and economics affects Real Estate Investment
Use household names and iconic companies, cities and buildings to help consolidate your appreciation of this exciting sector


Who will benefit from this course:

Graduates or undergraduates studying economics, finance.
Professionals working in Marketing or Accounting teams within Real Estate firms.
APC students.
Anyone interested in Real Estate.
School leavers/A-Level Students looking to gain an understanding of Real Estate.
Non cognate students who wish to transfer into Real Estate/Finance careers.


Course Outline

Module 1: What is and why buy Real Estate?

The property Market
The Size and Structure of the UK property market
The impact of Real Estate in the Economy


Module 2: The Real Estate Market System

The Space Market
The Asset Market
The Development Market


Module 3: How to value Real Estate

An Introduction to Financial Mathematics
The difference between Price, Value and Worth
Property Yield
Conventional Valuation Methods


Module 4: How to read a Real Estate Market Report

Property Market Indicators: Stock Indicators
Property Market Indicators: Investment Indicators


Module 5: Who works in Real Estate?

The build Environment by Cobalt Recruitment
Rea; Estate Agents
Examples of Real Estate Market Agents CVs
Real Estate Network


An Introduction to Real Estate (12 Hours Online Self-Study)

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p></p><p>The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.</p><p></p><p></p><p>This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.</p><p></p>Prerequisites<p></p><li>Understanding core data concepts.</li>  <li>Knowledge of working with relational data in the cloud.</li>  <li>Knowledge of working with non-relational data in the cloud.</li>   <li>Knowledge of data analysis and visualization concepts.</li>   <li>DP-900T00 Microsoft Azure Data Fundamentals is recommended<p></p></li></div><div id="course-pills-2"><h3>1 - Discover data analysis</h3> <ul> <li>Overview of data analysis</li> <li>Roles in data</li> <li>Tasks of a data analyst</li> </ul> <h3>2 - Get started building with Power BI</h3> <ul> <li>Use Power BI</li> <li>Building blocks of Power BI</li> <li>Tour and use the Power BI service</li> </ul> <h3>3 - Get data in Power BI</h3> <ul> <li>Get data from files</li> <li>Get data from relational data sources</li> <li>Create dynamic reports with parameters</li> <li>Get data from a NoSQL database</li> <li>Get data from online services</li> <li>Select a storage mode</li> <li>Get data from Azure Analysis Services</li> <li>Fix performance issues</li> <li>Resolve data import errors</li> </ul> <h3>4 - Clean, transform, and load data in Power BI</h3> <ul> <li>Shape the initial data</li> <li>Simplify the data structure</li> <li>Evaluate and change column data types</li> <li>Combine multiple tables into a single table</li> <li>Profile data in Power BI</li> <li>Use Advanced Editor to modify M code</li> </ul> <h3>5 - Design a semantic model in Power BI</h3> <ul> <li>Work with tables</li> <li>Create a date table</li> <li>Work with dimensions</li> <li>Define data granularity</li> <li>Work with relationships and cardinality</li> <li>Resolve modeling challenges</li> </ul> <h3>6 - Add measures to Power BI Desktop models</h3> <ul> <li>Create simple measures</li> <li>Create compound measures</li> <li>Create quick measures</li> <li>Compare calculated columns with measures</li> </ul> <h3>7 - Add calculated tables and columns to Power BI Desktop models</h3> <ul> <li>Create calculated columns</li> <li>Learn about row context</li> <li>Choose a technique to add a column</li> </ul> <h3>8 - Use DAX time intelligence functions in Power BI Desktop models</h3> <ul> <li>Use DAX time intelligence functions</li> <li>Additional time intelligence calculations</li> </ul> <h3>9 - Optimize a model for performance in Power BI</h3> <ul> <li>Review performance of measures, relationships, and visuals</li> <li>Use variables to improve performance and troubleshooting</li> <li>Reduce cardinality</li> <li>Optimize DirectQuery models with table level storage</li> <li>Create and manage aggregations</li> </ul> <h3>10 - Design Power BI reports</h3> <ul> <li>Design the analytical report layout</li> <li>Design visually appealing reports</li> <li>Report objects</li> <li>Select report visuals</li> <li>Select report visuals to suit the report layout</li> <li>Format and configure visualizations</li> <li>Work with key performance indicators</li> </ul> <h3>11 - Configure Power BI report filters</h3> <ul> <li>Apply filters to the report structure</li> <li>Apply filters with slicers</li> <li>Design reports with advanced filtering techniques</li> <li>Consumption-time filtering</li> <li>Select report filter techniques</li> <li>Case study - Configure report filters based on feedback</li> </ul> <h3>12 - Enhance Power BI report designs for the user experience</h3> <ul> <li>Design reports to show details</li> <li>Design reports to highlight values</li> <li>Design reports that behave like apps</li> <li>Work with bookmarks</li> <li>Design reports for navigation</li> <li>Work with visual headers</li> <li>Design reports with built-in assistance</li> <li>Tune report performance</li> <li>Optimize reports for mobile use</li> </ul> <h3>13 - Perform analytics in Power BI</h3> <ul> <li>Explore statistical summary</li> <li>Identify outliers with Power BI visuals</li> <li>Group and bin data for analysis</li> <li>Apply clustering techniques</li> <li>Conduct time series analysis</li> <li>Use the Analyze feature</li> <li>Create what-if parameters</li> <li>Use specialized visuals</li> </ul> <h3>14 - Create and manage workspaces in Power BI</h3> <ul> <li>Distribute a report or dashboard</li> <li>Monitor usage and performance</li> <li>Recommend a development life cycle strategy</li> <li>Troubleshoot data by viewing its lineage</li> <li>Configure data protection</li> </ul> <h3>15 - Manage semantic models in Power BI</h3> <ul> <li>Use a Power BI gateway to connect to on-premises data sources</li> <li>Configure a semantic model scheduled refresh</li> <li>Configure incremental refresh settings</li> <li>Manage and promote semantic models</li> <li>Troubleshoot service connectivity</li> <li>Boost performance with query caching (Premium)</li> </ul> <h3>16 - Create dashboards in Power BI</h3> <ul> <li>Configure data alerts</li> <li>Explore data by asking questions</li> <li>Review Quick insights</li> <li>Add a dashboard theme</li> <li>Pin a live report page to a dashboard</li> <li>Configure a real-time dashboard</li> <li>Set mobile view</li> </ul> <h3>17 - Implement row-level security</h3> <ul> <li>Configure row-level security with the static method</li> <li>Configure row-level security with the dynamic method</li> </ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans PL-300T00: Microsoft Power BI Data Analyst training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the PL-300T00: Microsoft Power BI Data Analyst course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Nexus Human

Powerbi

Business Analytics & Intelligence

Microsoft Power BI

Microsoft Power Platform

Microsoft BI

Data Analyst

PL-300T00 Microsoft Power BI Data Analyst

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			<h2>Overview of Data Analyst: Data Analysis in Excel</h2>		</div>
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					<div><p><span>Join our Data Analyst: Data Analysis in Excel course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Analyst: Data Analysis in Excel course has everything you need to get a great start in this sector.</span></p><p><span>Improving and moving forward is key to getting ahead personally. The Data Analyst: Data Analysis in Excel course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now!</span></p></div>
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			<h3>This <span>Data Analyst: Data Analysis in Excel</span> Course will help you to learn:</h3>		</div>
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					<div><p><span>This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Analyst: Data Analysis in Excel. Enrol today and complete the course to achieve a certificate that can change your career forever.</span></p></div>
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					<div><p>After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate.</p></div>
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					<div><h4><span>Certificate of Completion - Digital / PDF Certificate</span></h4>  
<p>After completing the <span>Data Analyst: Data Analysis in Excel course</span>, you can order your<span> CPD Accredited Digital / PDF Certificate for £5.99. </span></p>
<p><span>Certificate of Completion - Hard copy Certificate</span></p>
<p><span>You can get the CPD Accredited <b><i>Hard Copy Certificate for £12.99</i></b>.</span></p>
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<div><span>Shipping Charges:</span><span><span><br /></span></span></div>
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<li><p><span>Inside the UK: £3.99</span></p></li>
<li><p><span>International: £10.99</span></p></li>
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			<h3>Who Is This Course for?</h3>		</div>
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					<div><p><span>This Data Analyst: Data Analysis in Excel is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. </span></p><p><span>On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. </span></p><p><span>This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education.</span></p></div>
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					<div><p><span>You don't need any educational qualification or experience to enrol in the Data Analyst: Data Analysis in Excel course.</span></p>
<p><span>Do note: you must be at least 16 years old to enrol.</span></p>
<p><span>Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course.</span></p></div>
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					<div><p><span>The certification and skills you get from this </span><span>Data Analyst: Data Analysis in Excel Course</span><span> can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.</span></p></div>
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					<div id="elementor-tab-content-1721"><p>1.  You need to find the right course on our IOMH website at first. You can search for any course or find the course from the Courses section of our website.<br />2. Click on Take This Course button, and you will be directed to the Cart page.<br />3. You can update the course quantity and also remove any unwanted items in the CART and after that click on the Checkout option and enter your billing details.<br />4. Once the payment is made, you will receive an email with the login credentials, and you can start learning after logging into the portal.</p></div>
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					<div id="elementor-tab-content-1723"><p>You should receive your Digital Certificate within 24 hours after placing the order, and it will take 3-9 days to deliver the hard copies to your address if you are in the UK.</p><p>For International Delivery, it will take 20-25 days.</p><p>If you require any assistance, get in touch with our dedicated Customer Support team, and your queries/issues will be dealt with accordingly.</p></div>
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					<td><i></i></td>
					<td>Use Lookup Functions</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Trace Cells</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Watch and Evaluate Formulas</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
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					<td colspan="4">Automating Workbook Functionality</td>
				</tr>
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					<td><i></i></td>
					<td>Apply Data Validation</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Search for Invalid Data and Formulas with Errors</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Work with Macros</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Creating Sparklines and Mapping Data</td>
				</tr>
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					<td><i></i></td>
					<td>Create Sparklines</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>MapData</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
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					<td colspan="4">Forecasting Data</td>
				</tr>
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					<td><i></i></td>
					<td>Determine Potential Outcomes Using Data Tables</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Determine Potential Outcomes Using Scenarios</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Use the Goal Seek Feature</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Forecasting Data Trends</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
				</tbody></table></div>

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Overview of Data Analyst: Data Analysis in Excel
Join our Data Analyst: Data Analysis in Excel course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Analyst: Data Analysis in Excel course has everything you need to get a great start in this sector.
Improving and moving forward is key to getting ahead personally. The Data Analyst: Data Analysis in Excel course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now!
Get a Quick Look at The Course Content:
This Data Analyst: Data Analysis in Excel Course will help you to learn:
Learn strategies to boost your workplace efficiency.
Hone your skills to help you advance your career.
Acquire a comprehensive understanding of various topics and tips.
Learn in-demand skills that are in high demand among UK employers
This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Analyst: Data Analysis in Excel. Enrol today and complete the course to achieve a certificate that can change your career forever.
Details
Perks of Learning with IOMH
One-To-One Support from a Dedicated Tutor Throughout Your Course.
Study Online - Whenever and Wherever You Want.
Instant Digital/ PDF Certificate.
100% Money Back Guarantee.
12 Months Access.
Process of Evaluation
After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate.
Certificate of Achievement
Certificate of Completion - Digital / PDF Certificate
After completing the Data Analyst: Data Analysis in Excel course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. 
Certificate of Completion - Hard copy Certificate
You can get the CPD Accredited Hard Copy Certificate for £12.99.
Shipping Charges:
Inside the UK: £3.99
International: £10.99
Who Is This Course for?
This Data Analyst: Data Analysis in Excel is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. 
On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. 
This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education.
Requirements
You don't need any educational qualification or experience to enrol in the Data Analyst: Data Analysis in Excel course.
Do note: you must be at least 16 years old to enrol.
Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course.
Career Path
The certification and skills you get from this Data Analyst: Data Analysis in Excel Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.

 Course Curriculum

Modifying a Worksheet			
	Insert, Delete, and Adjust Cells, Columns, and Rows		00:10:00
	Search for and Replace Data		00:09:00
	Use Proofing and Research Tools		00:07:00
Working with Lists			
	Sort Data		00:10:00
	Filter Data		00:10:00
	Query Data with Database Functions		00:09:00
	Outline and Subtotal Data		00:09:00
Analyzing Data			
	Apply Intermediate Conditional Formatting		00:07:00
	Apply Advanced Conditional Formatting		00:05:00
Visualizing Data with Charts			
	Create Charts		00:13:00
	Modify and Format Charts		00:12:00
	Use Advanced Chart Features		00:12:00
Using PivotTables and PivotCharts			
	Create a PivotTable		00:13:00
	Analyze PivotTable Data		00:12:00
	Present Data with PivotCharts		00:07:00
	Filter Data by Using Timelines and Slicers		00:11:00
Working with Multiple Worksheets and Workbooks			
	Use Links and External References		00:12:00
	Use 3-D References		00:06:00
	Consolidate Data		00:05:00
Using Lookup Functions and Formula Auditing			
	Use Lookup Functions		00:12:00
	Trace Cells		00:09:00
	Watch and Evaluate Formulas		00:08:00
Automating Workbook Functionality			
	Apply Data Validation		00:13:00
	Search for Invalid Data and Formulas with Errors		00:04:00
	Work with Macros		00:18:00
Creating Sparklines and Mapping Data			
	Create Sparklines		00:07:00
	MapData		00:07:00
Forecasting Data			
	Determine Potential Outcomes Using Data Tables		00:08:00
	Determine Potential Outcomes Using Scenarios		00:09:00
	Use the Goal Seek Feature		00:04:00
	Forecasting Data Trends		00:05:00


IOMH - Institute of Mental Health

Big Data Analytics

Data Analysis Expressions

Data Management

Data Entry

Big Data

Business Data Analysis

Data Analyst: Data Analysis in Excel

<p><strong>Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £180 as a Gift-Enrol Now!!!</strong></p><p>Gain the essential skills for a<strong> Data Analyst </strong>role through this <strong>TWENTY-in-One career-oriented </strong>Professional Data Analyst Program from Apex Learning and position yourself competitively in the thriving job market for data analysts, which will see a <strong>20% growth by 2028</strong> (U.K. Bureau of Labor Statistics).</p><p>Power your<strong> Data Analyst </strong>career by learning the <strong>core principles</strong> of data analysis and gaining professional skills. You'll go through with a variety of data sources, project scenarios, and data analysis tools, including <strong>Excel</strong>, <strong>Power BI</strong>, <strong>SQL</strong>, <strong> Python</strong>, <strong>Google Data Studio</strong>,<strong> Tableau</strong> and <strong>SAS</strong>, gaining practical experience with data manipulation and applying analytical techniques.</p><p>Along with this Data Analyst : Data Analytics bundle, you will get 19 other premium courses.</p><p><strong>This Data Analyst : Data Analytics Bundle Consists of the following Premium courses:</strong></p><ul><li><strong>Course 01:</strong> Introduction to Data Analysis</li><li><strong>Course 02:</strong> Data Analytics with Tableau</li><li><strong>Course 03:</strong> Python for Data Analysis</li><li><strong>Course 04:</strong> Basic Google Data Studio</li><li><strong>Course 05:</strong> SQL NoSQL Big Data and Hadoop</li><li><strong>Course 06:</strong> Complete Microsoft Power BI 2021</li><li><strong>Course 07:</strong> Fundamentals of Business Analysis</li><li><strong>Course 08:</strong> Complete Introduction to Business Data Analysis Level 3</li><li><strong>Course 09:</strong> Business Intelligence and Data Mining Masterclass</li><li><strong>Course 10:</strong> Research Methods in Business</li><li><strong>Course 11:</strong> Statistical Analysis</li><li><strong>Course 12:</strong> Graph Theory Algorithms</li><li><strong>Course 13:</strong> Clinical Data Analysis with SAS</li><li><strong>Course 14:</strong> Data Analysis in Excel Level 3 Course</li><li><strong>Course 15:</strong> Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong>Course 16:</strong> PowerPoint Diploma</li><li><strong>Course 17:</strong> Data Protection and Data Security Level 2</li><li><strong>Course 18:</strong> Functional Skills IT</li><li><strong>Course 19:</strong> Decision Making and Critical Thinking</li></ul><p>So, enrol in this Data Analyst : Data Analytics Training now to advance your career!</p><p>This Data Analyst : Data Analytics bundle Does Not require any prior programming or statistical skills and is suitable for learners with or without college degrees.</p><p>The Data Analyst : Data Analytics bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Data Analyst : Data Analytics expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes.</p><p><strong>H</strong><strong>ow will I get my Certificate?</strong></p><p>After successfully completing the Data Analyst : Data Analytics Training, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p>P.S. The delivery charge inside the U.K. is £3.99, and the international students must pay £9.99.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        125 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in this Data Analyst : Data Analytics bundle.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Data Analyst : Data Analytics Trainingcourse has been designed to be fully compatible with tablets and smartphones.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Data Analyst : Data Analytics Training<strong>: </strong></p><p>This <strong>Data Analyst (Data Analytics) </strong>Bundle is ideal for anyone who wants to take their development to the next level and fast-track their career in any of the following roles:b</p><ul><li>Data analytics manager</li><li>Financial analyst</li><li>Marketing analyst</li><li>Systems analyst</li><li>Data scientist</li><li>Machine learning engineer</li><li>Data analytics consultant</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div> <p>You will get the PDF Certificate for the title course (<strong>Data Analysis</strong>) absolutely Free! </p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>Data Analysis</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £180 as a Gift-Enrol Now!!!
Gain the essential skills for a Data Analyst role through this TWENTY-in-One career-oriented Professional Data Analyst Program from Apex Learning and position yourself competitively in the thriving job market for data analysts, which will see a 20% growth by 2028 (U.K. Bureau of Labor Statistics).
Power your Data Analyst career by learning the core principles of data analysis and gaining professional skills. You'll go through with a variety of data sources, project scenarios, and data analysis tools, including Excel, Power BI, SQL,  Python, Google Data Studio, Tableau and SAS, gaining practical experience with data manipulation and applying analytical techniques.
Along with this Data Analyst : Data Analytics bundle, you will get 19 other premium courses.
This Data Analyst : Data Analytics Bundle Consists of the following Premium courses:
Course 01: Introduction to Data Analysis
Course 02: Data Analytics with Tableau
Course 03: Python for Data Analysis
Course 04: Basic Google Data Studio
Course 05: SQL NoSQL Big Data and Hadoop
Course 06: Complete Microsoft Power BI 2021
Course 07: Fundamentals of Business Analysis
Course 08: Complete Introduction to Business Data Analysis Level 3
Course 09: Business Intelligence and Data Mining Masterclass
Course 10: Research Methods in Business
Course 11: Statistical Analysis
Course 12: Graph Theory Algorithms
Course 13: Clinical Data Analysis with SAS
Course 14: Data Analysis in Excel Level 3 Course
Course 15: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Course 16: PowerPoint Diploma
Course 17: Data Protection and Data Security Level 2
Course 18: Functional Skills IT
Course 19: Decision Making and Critical Thinking
So, enrol in this Data Analyst : Data Analytics Training now to advance your career!
This Data Analyst : Data Analytics bundle Does Not require any prior programming or statistical skills and is suitable for learners with or without college degrees.
The Data Analyst : Data Analytics bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Data Analyst : Data Analytics expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes.
How will I get my Certificate?
After successfully completing the Data Analyst : Data Analytics Training, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.
PDF Certificate: Free (For The Title Course)
Hard Copy Certificate: Free (For The Title Course)
P.S. The delivery charge inside the U.K. is £3.99, and the international students must pay £9.99.
 CPD 
125 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Anyone from any background can enrol in this Data Analyst : Data Analytics bundle.
 Requirements 
This Data Analyst : Data Analytics Trainingcourse has been designed to be fully compatible with tablets and smartphones.
 Career path 
Data Analyst : Data Analytics Training: 
This Data Analyst (Data Analytics) Bundle is ideal for anyone who wants to take their development to the next level and fast-track their career in any of the following roles:b
Data analytics manager
Financial analyst
Marketing analyst
Systems analyst
Data scientist
Machine learning engineer
Data analytics consultant
 Certificates 
Certificate of completion
 Digital certificate - Included 
You will get the PDF Certificate for the title course (Data Analysis) absolutely Free! 
Certificate of completion
 Hard copy certificate - Included 
You will get the Hard Copy certificate for the title course (Data Analysis) absolutely Free! Other Hard Copy certificates are available for £10 each. 
Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Apex Learning

Data Analyst : Data Analytics Training

dbrownconsulting

Data Engineering

Advanced Data Analysis and Reconciliation

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					<div><p>The comprehensive Clinical Data Analysis with SAS   has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Clinical Data Analysis with SAS   today, and learn from the very best the industry has to offer!</p></div>
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					<div><p>This best selling Clinical Data Analysis with SAS   has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Clinical Data Analysis with SAS   is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The Clinical Data Analysis with SAS   is CPD-accredited, so you can be confident you're completing a quality training course  will boost your CV and enhance your career potential. The Clinical Data Analysis with SAS   is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the Clinical Data Analysis with SAS  , you will be awarded a certificate of completion  as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Clinical Data Analysis with SAS   will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the Clinical Data Analysis with SAS   to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Clinical Data Analysis with SAS

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			<h2>Overview</h2>		</div>
				</div>
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					<div><p><span>Join our Business Data Analysis course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Business Data Analysis course has everything you need to get a great start in this sector.</span></p><p><span>Improving and moving forward is key to getting ahead personally. The Business Data Analysis course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now!</span></p></div>
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			<h4>You Will Learn Following Things: </h4>  		</div>
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				<div>
					<ul>
							<li>
											<span>
							<i></i>						</span>
										<span>Learn strategies to boost your workplace efficiency.</span>
									</li>
								<li>
											<span>
							<i></i>						</span>
										<span>Hone your skills to help you advance your career.</span>
									</li>
								<li>
											<span>
							<i></i>						</span>
										<span>Acquire a comprehensive understanding of various topics and tips.</span>
									</li>
								<li>
											<span>
							<i></i>						</span>
										<span>Learn in-demand skills that are in high demand among UK employers</span>
									</li>
						</ul>
				</div>
				</div>
				<div>
				<div>
					<div><p><span>This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Business Data Analysis. Enrol today and complete the course to achieve a certificate that can change your career forever.</span></p></div>
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			<h2>Details
</h2>		</div>
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			<h4>Perks of Learning with IOMH</h4>  		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
							<i></i>						</span>
										<span>One-to-one support from a dedicated tutor throughout your course.</span>
									</li>
								<li>
											<span>
							<i></i>						</span>
										<span>Study online - whenever and wherever you want.</span>
									</li>
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											<span>
							<i></i>						</span>
										<span>Instant Digital/ PDF certificate</span>
									</li>
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											<span>
							<i></i>						</span>
										<span>100% money back guarantee</span>
									</li>
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											<span>
							<i></i>						</span>
										<span>12 months access</span>
									</li>
						</ul>
				</div>
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			<h4>Process of Evaluation</h4>  		</div>
				</div>
				<div>
				<div>
					<div><p>After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate.</p></div>
				</div>
				</div>
				<div>
				<div>
			<h4>Certificate of Achievement</h4>  		</div>
				</div>
				<div>
				<div>
					<div><p><span>After completing the </span><b>Business Data Analysis course</b><span>, you will receive your</span><b> CPD-accredited Digital/PDF Certificate for £5.99. </b><span>To get the </span><b>hardcopy certificate for £12.99, </b><span>you must also pay the shipping charge of just</span><b> £3.99 (UK) and £10.99 (International).</b></p></div>
				</div>
				</div>
				<div>
				<div>
			<h4>Who Is This Course for?</h4>  		</div>
				</div>
				<div>
				<div>
					<div><p><span>This Business Data Analysis is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. </span></p><p><span>On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. </span></p><p><span>This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education.</span></p></div>
				</div>
				</div>
				<div>
				<div>
			<h4>Requirements</h4>  		</div>
				</div>
				<div>
				<div>
					<div><p><span>There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Business Data Analysis course.</span></p><p><span>Do note: you must be at least 16 years old to enrol.</span></p><p><span>Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course.</span></p></div>
				</div>
				</div>
				<div>
				<div>
			<h4>Career path</h4>  		</div>
				</div>
				<div>
				<div>
					<div><p><span>The certification and skills you get from this </span><span>Business Data Analysis Course</span><span> can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.</span></p></div>
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	<span>Course Curriculum</span>
</h3>

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					<td colspan="4">Business Data Analysis</td>
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					<td>Module 01: Introduction to Business Analysis</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
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					<td>Module 2: Business Environment</td>
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					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 3: Business Processes</td>
					<td> </td>
					<td><span><i></i> 00:47:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 4: Business Analysis Planning and Monitoring</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 5: Strategic Analysis and Product Scope</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 6: Solution Evaluation</td>
					<td> </td>
					<td><span><i></i> 00:27:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 7: Investigation Techniques</td>
					<td> </td>
					<td><span><i></i> 00:48:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 8: Ratio Analysis</td>
					<td> </td>
					<td><span><i></i> 00:29:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 9: Stakeholder Analysis and Management</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 10: Process Improvement with Gap Analysis</td>
					<td> </td>
					<td><span><i></i> 00:28:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 11: Documenting and Managing Requirements</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 12: Business Development and Succession Planning</td>
					<td> </td>
					<td><span><i></i> 00:27:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 13: Planning &amp; Forecasting Operations</td>
					<td> </td>
					<td><span><i></i> 00:23:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 14: Business Writing Skills</td>
					<td> </td>
					<td><span><i></i> 00:39:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Mock Exam</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mock Exam - Business Data Analysis</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Final Exam</td>
				</tr>
				</tbody></table></div>

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

Overview
Join our Business Data Analysis course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Business Data Analysis course has everything you need to get a great start in this sector.
Improving and moving forward is key to getting ahead personally. The Business Data Analysis course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now!
You Will Learn Following Things:
Learn strategies to boost your workplace efficiency.
Hone your skills to help you advance your career.
Acquire a comprehensive understanding of various topics and tips.
Learn in-demand skills that are in high demand among UK employers
This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Business Data Analysis. Enrol today and complete the course to achieve a certificate that can change your career forever.
Details

Perks of Learning with IOMH
One-to-one support from a dedicated tutor throughout your course.
Study online - whenever and wherever you want.
Instant Digital/ PDF certificate
100% money back guarantee
12 months access
Process of Evaluation
After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate.
Certificate of Achievement
After completing the Business Data Analysis course, you will receive your CPD-accredited Digital/PDF Certificate for £5.99. To get the hardcopy certificate for £12.99, you must also pay the shipping charge of just £3.99 (UK) and £10.99 (International).
Who Is This Course for?
This Business Data Analysis is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. 
On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. 
This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education.
Requirements
There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Business Data Analysis course.
Do note: you must be at least 16 years old to enrol.
Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course.
Career path
The certification and skills you get from this Business Data Analysis Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.
 Course Curriculum

Business Data Analysis			
	Module 01: Introduction to Business Analysis		00:17:00
	Module 2: Business Environment		00:19:00
	Module 3: Business Processes		00:47:00
	Module 4: Business Analysis Planning and Monitoring		00:30:00
	Module 5: Strategic Analysis and Product Scope		00:31:00
	Module 6: Solution Evaluation		00:27:00
	Module 7: Investigation Techniques		00:48:00
	Module 8: Ratio Analysis		00:29:00
	Module 9: Stakeholder Analysis and Management		00:25:00
	Module 10: Process Improvement with Gap Analysis		00:28:00
	Module 11: Documenting and Managing Requirements		00:31:00
	Module 12: Business Development and Succession Planning		00:27:00
	Module 13: Planning & Forecasting Operations		00:23:00
	Module 14: Business Writing Skills		00:39:00
Mock Exam			
	Mock Exam - Business Data Analysis		00:20:00
Final Exam			

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