Machine Learning: Predictive Analysis for Business Decisions

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Business leaders will learn of the various types of machine learning, and" /><meta name="keywords" content="Machine learning, big data, data science, artificial intelligence, AI, computational intelligence, deep learning, 978-1-7281-7749-6, EDP582, This course provides an overview of machine learning in" /></head> <body class="canvas"> <form method="post" action="./ContentDetails.aspx?id=72F4692104C84E1FA1040ECD20E8B536&utm_source=iaw&utm_medium=web_l_20210411&utm_campaign=ml_PicsAd" id="Form1"> <div class="aspNetHidden"> <input type="hidden" name="RadScriptManager1_TSM" id="RadScriptManager1_TSM" value="" /> <input type="hidden" name="__EVENTTARGET" id="__EVENTTARGET" value="" /> <input type="hidden" name="__EVENTARGUMENT" id="__EVENTARGUMENT" value="" /> <input type="hidden" name="__VIEWSTATE" id="__VIEWSTATE" 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} }); } //Set help Link if ($('#lnkHelp').length > 0) { $.ajax({ url: '/Menus/TopLevelMenu/GetHelpUrl', dataType: 'text', success: function (help_url) { $('#lnkHelp').attr('href', help_url); if(help_url.lastIndexOf('401') == -1) { $('#help-list-item').hide(); } } }); } </script> <div class="brand-bar-container" role="presentation"> <div class="container hidden-sm hidden-xs brand-bar"> <div class="row"> <div class="col-xs-12"> <div class="brand-bar-logo" role="presentation"></div> <div class="brand-bar-photo" role="presentation"></div> </div> </div> </div> </div> </header> <div class="container"> <div id="content" class="row" tabindex="-1" role="main"> <div class="col-md-8"> <div class="portlet"> <h1>Machine Learning: Predictive Analysis for Business Decisions</h1> <ul class="list-inline"> <li> <strong> Course Program </strong> </li> <li class="social-sharing"> </li> </ul> <p> <p>This course provides an overview of machine learning in the age of big data, cloud computing, and our data-saturated society. Business leaders will learn of the various types of machine learning, and how they can be used with a variety of enterprise data holdings and publicly available data to develop deeper insights in the business environment;  understand basic computational intelligence paradigms, and how machine learning is integral to the field;  learn the technical vocabulary and high-level concepts of machine learning in a manner that demystifies the topic and enables them to ask the right questions on the deployment of machine learning into business operations.</p><p><em>What you will learn:</em></p><ul><li>Examine the fundamental types of machine learning that drive business insights</li><li>Explore how to manage multi-facet enterprise data to enable machine learning</li><li>Review the application of data mining and diagnostic analytics to measure business performance</li><li>Gain an understanding of software, algorithms, and models</li><li>Understand the concepts and techniques necessary for deploying scalable machine learning into business processes</li></ul><p><strong>Courses included in this program</strong>:</p><ul><li><a href="https://iln.ieee.org/Public/ContentDetails.aspx?id=CD3308F8F1AF474BB3D4E911467883A9" rel="noopener noreferrer" target="_blank">Machine Learning in the Age of Enterprise Big Data</a></li><li><a href="https://iln.ieee.org/Public/Contentdetails.aspx?id=07C34DCA38434F359A940C33BFB1D8B1" rel="noopener noreferrer" target="_blank">Machine Learning in a Data-Driven Business Environment</a></li><li><a href="https://iln.ieee.org/Public/Contentdetails.aspx?id=0FBCDF731EAA402FA1F24D51317770A8" rel="noopener noreferrer" target="_blank">Sound Business Practices for Data Mining and Predictive Analysis</a></li><li><a href="https://iln.ieee.org/Public/ContentDetails.aspx?id=E2E7E75137CC437E87FD38981EE2161F" rel="noopener noreferrer" target="_blank">Machine Learning Algorithms, Models, and Systems Integration</a></li><li><a href="https://iln.ieee.org/Public/ContentDetails.aspx?id=37CE84124A00423DB9D4CA5F222178F8" rel="noopener noreferrer" target="_blank">Machine Learning Platforms, Technology, and Tools</a></li></ul><p><strong>Course Program Length</strong>: 5 hours</p><p><strong>Who Should Attend</strong>: Computer engineers, business executives, industry executives,  industry leaders, business leaders,  technical managers, data scientists, and data engineers</p><p><strong><span style="color: rgb(226, 80, 65);">Instructor</span></strong></p><p><strong>Grant Scott</strong>, Assistant Professor in the Center for Geospatial Intelligence (CGI) and the Electrical Engineering and Computer Science Department, University of Missouri</p><p data-empty="true"><strong>Publication Year</strong>: 2020</p><p data-empty="true"><strong>ISBN</strong>: 978-1-7281-7749-6</p><p data-empty="true">Upon successful completion of this course program, you are eligible to receive a <a href="http://innovationatwork.ieee.org/wp-content/uploads/2022/06/21-EA-308f-EABadgingFlyer-R9.pdf" rel="noopener noreferrer" target="_blank">digital badge</a> that can be shared on LinkedIn and other social networks.   If you would like to request a badge for this program, please contact us:  eab-ceuadmin@ieee.org.</p> </p> <hr /> <script type="text/javascript"> function XploreLogin(strURL) { window.location.href = strURL; 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} ); } } ); }) </script> </div> <div class="content-thumbnail"> <img id="MainContent_ucContentMetaData_FormView1_MImage1" class="img-thumbnail ieee-content-image" src="/CServer//Image/72F4692104C84E1FA1040ECD20E8B536/EDP590_bigstock-Automation-Software-Technology-258588526.jpg" alt="Machine Learning: Predictive Analysis for Business Decisions" /> </div> <ul class="list-group"> <li class="list-group-item"> Course Provider: <strong>Educational Activities</strong> </li> <li class="list-group-item"> Course Number: <strong>EDP582CP</strong> </li> <li class="list-group-item"> Credits: <strong>0.5 CEU/ 5 PDH</strong> </li> </ul> </div> </div> </div> </div> <footer class="container-fluid"> <div class="row"> <div id="mgFooter" class="col-xs-12"> <script type="text/javascript"> //Adjust the pull-right class function changePullRight() { if (window.location.href.indexOf("managesectiontimeline") != -1 && document.getElementsByClassName('btn-group pull-right')) { document.getElementsByClassName('btn-group pull-right')[0].style.left = "-235px"; 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