BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Canada/Mountain BEGIN:DAYLIGHT DTSTART:20210314T030000 TZOFFSETFROM:-0700 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:MDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20211107T010000 TZOFFSETFROM:-0600 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:MST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20210621T170900Z UID:77E593BD-6765-48E8-9D92-B3AE4BD45A13 DTSTART;TZID=Canada/Mountain:20210701T010500 DTEND;TZID=Canada/Mountain:20210705T235900 DESCRIPTION:IEEE Northern Canada Section (NCS) and IEEE Continuing Educatio n Committee (CEC) of the Educational Activities Board (EAB) are organizing and sponsoring this online course program\, eligible for CUE credits.\n\n The course program [Machine Learning: Predictive Analysis for Business Dec isions](https://iln.ieee.org/Public/ContentDetails.aspx?id=72F4692104C84E1 FA1040ECD20E8B536) is available to all NCS members at 10% of its cost\, to be taken individually\, for the time window July 1-31\, 2021.\n\nThis cou rse provides an overview of machine learning in the age of big data\, clou d 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 develo p deeper insights in the business environment\; understand basic computati onal 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 th e right questions on the deployment of machine learning into business oper ations.\n\nCourses included in this program:\n\n- Machine Learning in the Age of Enterprise Big Data\n- Machine Learning in a Data-Driven Business E nvironment\n- Sound Business Practices for Data Mining and Predictive Anal ysis\n- Machine Learning Algorithms\, Models\, and Systems Integration\n- Machine Learning Platforms\, Technology\, and Tools\n\nThe course is part of the IEEE eLearning program\, offered through the IEEE Learning Network (ILN).\n\nNCS members cost is approximately 10% of the announced course pr ogram cost\, converted from US$ to CAD$.\n\nTo join IEEE\, please [visit t he IEEE website](https://www.ieee.org/membership/join/index.html?WT.mc_id= hc_join).\n\nPlease register no later than June 21\, 2021 !\n\nThe course will be open between July 1 and July 31\, 2021 !\n\nCo-sponsored by: Educa tional Activities Board of the IEEE\n\nAgenda: \nThis course program inclu des the following courses:\n\n- Machine Learning in the Age of Enterprise Big Data\n- Machine Learning in a Data-Driven Business Environment\n- Soun d Business Practices for Data Mining and Predictive Analysis\n- Machine Le arning Algorithms\, Models\, and Systems Integration\n- Machine Learning P latforms\, Technology\, and Tools\n\nEdmonton\, Alberta\, Canada\, Virtual : https://events.vtools.ieee.org/m/273630 LOCATION:Edmonton\, Alberta\, Canada\, Virtual: https://events.vtools.ieee. org/m/273630 ORGANIZER:marinova@ieee.org SEQUENCE:19 SUMMARY:Northern Canada Section ILN Course Program URL;VALUE=URI:https://events.vtools.ieee.org/m/273630 X-ALT-DESC:Description: <br /><p>IEEE Northern Canada Section (NCS) and IEE E Continuing Education Committee (CEC) of the Educational Activities Board (EAB) are organizing and sponsoring this online course program\, eligible for CUE credits.&nbsp\;</p>\n<p>The course program <a href="https://iln.i eee.org/Public/ContentDetails.aspx?id=72F4692104C84E1FA1040ECD20E8B536"><e m>Machine Learning: Predictive Analysis for Business Decisions</em></a> is available to all NCS members at 10% of its cost\, to be taken individuall y\, for the time window July 1-31\, 2021.</p>\n<p>This course provides an overview of machine learning in the age of big data\, cloud computing\, an d our data-saturated society. Business leaders will learn of the various t ypes of machine learning\, and how they can be used with a variety of ente rprise data holdings and publicly available data to develop deeper insight s in the business environment\; &nbsp\;understand basic computational inte lligence paradigms\, and how machine learning is integral to the field\; & nbsp\;learn the technical vocabulary and high-level concepts of machine le arning in a manner that demystifies the topic and enables them to ask the right questions on the deployment of machine learning into business operat ions.</p>\n<p>Courses included in this program:</p>\n<ul>\n<li>Machine Lea rning in the Age of Enterprise Big Data</li>\n<li>Machine Learning in a Da ta-Driven Business Environment</li>\n<li>Sound Business Practices for Data Mining and Predictive Analysis</li>\n<li>Machine Learning Algorithms\, Mo dels\, and Systems Integration</li>\n<li>Machine Learning Platforms\, Tech nology\, and Tools</li>\n</ul>\n<p>The course is part of the <strong><em>I EEE eLearning</em></strong>&nbsp\;program\, offered through the&nbsp\;<str ong><em>IEEE Learning Network (ILN)</em></strong>.&nbsp\;</p>\n<p>NCS memb ers cost is approximately 10% of the announced course program cost\, conve rted from US$ to CAD$.&nbsp\;</p>\n<p>To join IEEE\, please&nbsp\;<a href= "https://www.ieee.org/membership/join/index.html?WT.mc_id=hc_join">visit t he IEEE website</a>.&nbsp\;</p>\n<p><span style="text-decoration: underlin e\;"><span style="color: #e03e2d\; text-decoration: underline\;">Please re gister no later than June 21\, 2021 !</span></span></p>\n<p><span style="t ext-decoration: underline\; color: #e03e2d\;">The course will be open betw een July 1 and July 31\, 2021 !</span></p><br /><br />Agenda: <br /><p><st rong>This course program includes the following courses:</strong></p>\n<ul >\n<li>Machine Learning in the Age of Enterprise Big Data</li>\n<li>Machin e Learning in a Data-Driven Business Environment</li>\n<li>Sound Business Practices for Data Mining and Predictive Analysis</li>\n<li>Machine Learni ng Algorithms\, Models\, and Systems Integration</li>\n<li>Machine Learnin g Platforms\, Technology\, and Tools</li>\n</ul> END:VEVENT END:VCALENDAR