{"id":3332,"date":"2024-10-14T12:04:48","date_gmt":"2024-10-14T12:04:48","guid":{"rendered":"https:\/\/nepttp.avidakizomba.co.za\/?page_id=3332"},"modified":"2026-04-15T13:38:10","modified_gmt":"2026-04-15T11:38:10","slug":"masters-programmes","status":"publish","type":"page","link":"https:\/\/www.escience.ac.za\/index.php\/masters-programmes\/","title":{"rendered":"Masters Programmes"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"3332\" class=\"elementor elementor-3332\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8a8b9d6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8a8b9d6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-56bb596\" data-id=\"56bb596\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6a14fda elementor-widget elementor-widget-slider_revolution\" data-id=\"6a14fda\" data-element_type=\"widget\" data-widget_type=\"slider_revolution.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\r\n\t\t<div class=\"wp-block-themepunch-revslider\">\n\t\t\t<!-- START Masters Programmes REVOLUTION SLIDER 6.3.9 --><p class=\"rs-p-wp-fix\"><\/p>\n\t\t\t<rs-module-wrap id=\"rev_slider_3_1_wrapper\" data-source=\"gallery\" style=\"background:transparent;padding:0;margin:0px auto;margin-top:0;margin-bottom:0;\">\n\t\t\t\t<rs-module id=\"rev_slider_3_1\" style=\"\" data-version=\"6.3.9\">\n\t\t\t\t\t<rs-slides>\n\t\t\t\t\t\t<rs-slide data-key=\"rs-3\" data-title=\"Home\" data-anim=\"ei:d;eo:d;s:1000;r:0;t:fade;sl:0;\">\n\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" src=\"\/\/www.escience.ac.za\/wp-content\/uploads\/revslider\/about-us-12\/Slider-BG-Template-About-Us1.jpg\" title=\"Slider-BG-Template-About-Us1.jpg\" width=\"1920\" height=\"296\" class=\"rev-slidebg\" data-no-retina>\n<!--\n\t\t\t\t\t\t\t--><a\n\t\t\t\t\t\t\t\tid=\"slider-3-slide-3-layer-0\" \n\t\t\t\t\t\t\t\tclass=\"rs-layer rev-btn icon-right rev-btn\"\n\t\t\t\t\t\t\t\thref=\"https:\/\/www.escience.ac.za\/index.php\/about-us\/\" target=\"_self\" 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rev-btn\"\n\t\t\t\t\t\t\t\thref=\"https:\/\/www.escience.ac.za\/index.php\/contact\/\" target=\"_self\" rel=\"nofollow\"\n\t\t\t\t\t\t\t\tdata-type=\"button\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:r;xo:348px,0,348px,30px;yo:207px,502px,502px,298px;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:14,18,18,12;l:65;fw:500;\"\n\t\t\t\t\t\t\t\tdata-dim=\"minh:0px,none,0px,none;\"\n\t\t\t\t\t\t\t\tdata-rsp_bd=\"off\"\n\t\t\t\t\t\t\t\tdata-padding=\"r:20,30,30,10;l:20,30,30,10;\"\n\t\t\t\t\t\t\t\tdata-border=\"bor:3px,3px,3px,3px;\"\n\t\t\t\t\t\t\t\tdata-frame_0=\"y:50,43,43,19;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"st:900;sp:1000;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;\"\n\t\t\t\t\t\t\t\tdata-frame_hover=\"bgc:#485d57;bor:3px,3px,3px,3px;sp:100;e:power1.inOut;bri:100%;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:13;background-color:#70984b;font-family:Roboto;\"\n\t\t\t\t\t\t\t>Contact Us \n\t\t\t\t\t\t\t<\/a><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-3-slide-3-layer-4\" \n\t\t\t\t\t\t\t\tdata-type=\"shape\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:20,17,17,7;l:0,21,21,9;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:4000px,3500px,3500px,1640px;h:254px,222px,222px,103px;\"\n\t\t\t\t\t\t\t\tdata-border=\"bor:40px,40px,40px,40px;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:9;background:linear-gradient(rgba(2,2,2,0.7) 0%, rgba(66,66,66,0.7) 30%, rgba(215,215,215,0) 100%);\"\n\t\t\t\t\t\t\t> \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><a\n\t\t\t\t\t\t\t\tid=\"slider-3-slide-3-layer-5\" \n\t\t\t\t\t\t\t\tclass=\"rs-layer\"\n\t\t\t\t\t\t\t\thref=\"https:\/\/www.escience.ac.za\/\" target=\"_self\"\n\t\t\t\t\t\t\t\tdata-type=\"image\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;yo:20px,17px,17px,69px;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:20,17,17,7;l:0,21,21,9;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:314px,274px,274px,370px;h:155px,135px,135px,183px;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:14;\"\n\t\t\t\t\t\t\t><img decoding=\"async\" src=\"\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/escience-logo-16-July-2018-WHITE-Vectorise.png\" width=\"817\" height=\"404\" data-no-retina> \n\t\t\t\t\t\t\t<\/a><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-3-slide-3-layer-6\" \n\t\t\t\t\t\t\t\tdata-type=\"shape\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:20,17,17,7;l:0,21,21,9;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:4000px,3500px,3500px,1640px;h:2400,2100,2100,984;\"\n\t\t\t\t\t\t\t\tdata-blendmode=\"multiply\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:8;background-color:rgba(255,255,255,0.5);\"\n\t\t\t\t\t\t\t> \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><a\n\t\t\t\t\t\t\t\tid=\"slider-3-slide-3-layer-7\" \n\t\t\t\t\t\t\t\tclass=\"rs-layer rev-btn icon-right rev-btn\"\n\t\t\t\t\t\t\t\thref=\"https:\/\/www.escience.ac.za\/index.php\/our-institutions\/\" target=\"_self\" rel=\"nofollow\"\n\t\t\t\t\t\t\t\tdata-type=\"button\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;xo:46px,0,46px,35px;yo:207px,502px,502px,298px;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:14,18,18,12;l:65;fw:500;\"\n\t\t\t\t\t\t\t\tdata-dim=\"minh:0px,none,0px,none;\"\n\t\t\t\t\t\t\t\tdata-rsp_bd=\"off\"\n\t\t\t\t\t\t\t\tdata-padding=\"r:20,30,30,10;l:20,30,30,10;\"\n\t\t\t\t\t\t\t\tdata-border=\"bor:3px,3px,3px,3px;\"\n\t\t\t\t\t\t\t\tdata-frame_0=\"y:50,43,43,19;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"st:900;sp:1000;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;\"\n\t\t\t\t\t\t\t\tdata-frame_hover=\"bgc:#485d57;bor:3px,3px,3px,3px;sp:100;e:power1.inOut;bri:100%;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:10;background-color:#70984b;font-family:Roboto;\"\n\t\t\t\t\t\t\t>Our Institutions \n\t\t\t\t\t\t\t<\/a><!--\n\n\t\t\t\t\t\t\t--><a\n\t\t\t\t\t\t\t\tid=\"slider-3-slide-3-layer-8\" \n\t\t\t\t\t\t\t\tclass=\"rs-layer rev-btn icon-right rev-btn\"\n\t\t\t\t\t\t\t\thref=\"https:\/\/www.escience.ac.za\/\" target=\"_self\" rel=\"nofollow\"\n\t\t\t\t\t\t\t\tdata-type=\"button\"\n\t\t\t\t\t\t\t\tdata-xy=\"xo:360px,0,360px,30px;yo:207px,502px,502px,298px;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:14,18,18,12;l:65;fw:500;\"\n\t\t\t\t\t\t\t\tdata-dim=\"minh:0px,none,0px,none;\"\n\t\t\t\t\t\t\t\tdata-rsp_bd=\"off\"\n\t\t\t\t\t\t\t\tdata-padding=\"r:20,30,30,10;l:20,30,30,10;\"\n\t\t\t\t\t\t\t\tdata-border=\"bor:3px,3px,3px,3px;\"\n\t\t\t\t\t\t\t\tdata-frame_0=\"y:50,43,43,19;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"st:900;sp:1000;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;\"\n\t\t\t\t\t\t\t\tdata-frame_hover=\"bgc:#485d57;bor:3px,3px,3px,3px;sp:100;e:power1.inOut;bri:100%;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:11;background-color:#70984b;font-family:Roboto;\"\n\t\t\t\t\t\t\t>Home \n\t\t\t\t\t\t\t<\/a><!--\n-->\t\t\t\t\t\t<\/rs-slide>\n\t\t\t\t\t<\/rs-slides>\n\t\t\t\t\t<rs-static-layers><!--\n\t\t\t\t\t--><\/rs-static-layers>\n\t\t\t\t<\/rs-module>\n\t\t\t\t<script type=\"text\/javascript\">\n\t\t\t\t\tsetREVStartSize({c: 'rev_slider_3_1',rl:[1240,1024,1024,480],el:[300,600,600,740],gw:[1170,1024,1024,480],gh:[300,600,600,740],type:'standard',justify:'',layout:'fullwidth',mh:\"0\"});\n\t\t\t\t\tvar\trevapi3,\n\t\t\t\t\t\ttpj;\n\t\t\t\t\tfunction revinit_revslider31() {\n\t\t\t\t\tjQuery(function() {\n\t\t\t\t\t\ttpj = jQuery;\n\t\t\t\t\t\trevapi3 = tpj(\"#rev_slider_3_1\");\n\t\t\t\t\t\tif(revapi3==undefined || revapi3.revolution == undefined){\n\t\t\t\t\t\t\trevslider_showDoubleJqueryError(\"rev_slider_3_1\");\n\t\t\t\t\t\t}else{\n\t\t\t\t\t\t\trevapi3.revolution({\n\t\t\t\t\t\t\t\tsliderLayout:\"fullwidth\",\n\t\t\t\t\t\t\t\tvisibilityLevels:\"1240,1024,1024,480\",\n\t\t\t\t\t\t\t\tgridwidth:\"1170,1024,1024,480\",\n\t\t\t\t\t\t\t\tgridheight:\"300,600,600,740\",\n\t\t\t\t\t\t\t\tspinner:\"spinner0\",\n\t\t\t\t\t\t\t\tperspective:600,\n\t\t\t\t\t\t\t\tperspectiveType:\"local\",\n\t\t\t\t\t\t\t\teditorheight:\"300,600,960,740\",\n\t\t\t\t\t\t\t\tresponsiveLevels:\"1240,1024,1024,480\",\n\t\t\t\t\t\t\t\tprogressBar:{disableProgressBar:true},\n\t\t\t\t\t\t\t\tnavigation: {\n\t\t\t\t\t\t\t\t\tonHoverStop:false\n\t\t\t\t\t\t\t\t},\n\t\t\t\t\t\t\t\tfallbacks: {\n\t\t\t\t\t\t\t\t\tallowHTML5AutoPlayOnAndroid:true\n\t\t\t\t\t\t\t\t},\n\t\t\t\t\t\t\t});\n\t\t\t\t\t\t}\n\t\t\t\t\t\t\n\t\t\t\t\t});\n\t\t\t\t\t} \/\/ End of RevInitScript\n\t\t\t\tvar once_revslider31 = false;\n\t\t\t\tif (document.readyState === \"loading\") {document.addEventListener('readystatechange',function() { if((document.readyState === \"interactive\" || document.readyState === \"complete\") && !once_revslider31 ) { once_revslider31 = true; revinit_revslider31();}});} else {once_revslider31 = true; revinit_revslider31();}\n\t\t\t\t<\/script>\n\t\t\t<\/rs-module-wrap>\n\t\t\t<!-- END REVOLUTION SLIDER -->\n<\/div>\r\n\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-d7dacf1 elementor-section-full_width elementor-section-stretched elementor-section-height-default elementor-section-height-default\" data-id=\"d7dacf1\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d0c01fe\" data-id=\"d0c01fe\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-20f6660 elementor-widget elementor-widget-heading\" data-id=\"20f6660\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Master's Programmes<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t<div class=\"elementor-element elementor-element-0fab5bd e-flex e-con-boxed e-con e-parent\" data-id=\"0fab5bd\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6f8f24f1 elementor-widget elementor-widget-eael-adv-tabs\" data-id=\"6f8f24f1\" data-element_type=\"widget\" data-widget_type=\"eael-adv-tabs.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t        <div data-scroll-on-click=\"no\" data-scroll-speed=\"300\" id=\"eael-advance-tabs-6f8f24f1\" class=\"eael-advance-tabs eael-tabs-horizontal eael-tab-auto-active  active-caret-on\" data-tabid=\"6f8f24f1\">\n            <div class=\"eael-tabs-nav\">\n                <ul class=\"\" role=\"tablist\">\n                                            <li id=\"msc\" class=\"active-default eael-tab-item-trigger eael-tab-nav-item\" aria-selected=\"true\" data-tab=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"msc-tab\" aria-expanded=\"false\">\n                            \n                            \n                            \n                                                            <span class=\"eael-tab-title title-after-icon\" >MSc<\/span>                                                    <\/li>\n                                            <li id=\"ma\" class=\"inactive eael-tab-item-trigger eael-tab-nav-item\" aria-selected=\"false\" data-tab=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"ma-tab\" aria-expanded=\"false\">\n                            \n                            \n                            \n                                                            <span class=\"eael-tab-title title-after-icon\" >MA<\/span>                                                    <\/li>\n                                            <li id=\"general-information\" class=\"inactive eael-tab-item-trigger eael-tab-nav-item\" aria-selected=\"false\" data-tab=\"3\" role=\"tab\" tabindex=\"-1\" aria-controls=\"general-information-tab\" aria-expanded=\"false\">\n                            \n                            \n                            \n                                                            <span class=\"eael-tab-title title-after-icon\" >General Information<\/span>                                                    <\/li>\n                                    <\/ul>\n            <\/div>\n            \n            <div class=\"eael-tabs-content\">\n\t\t        \n                    <div id=\"msc-tab\" class=\"clearfix eael-tab-content-item active-default\" data-title-link=\"msc-tab\">\n\t\t\t\t        <style>.elementor-3532 .elementor-element.elementor-element-e814fc2{--display:flex;--background-transition:0.3s;--padding-top:0px;--padding-bottom:0px;--padding-left:0px;--padding-right:0px;}.elementor-widget-accordion .elementor-accordion-icon, .elementor-widget-accordion .elementor-accordion-title{color:var( --e-global-color-primary );}.elementor-widget-accordion .elementor-accordion-icon svg{fill:var( --e-global-color-primary );}.elementor-widget-accordion .elementor-active .elementor-accordion-icon, .elementor-widget-accordion .elementor-active .elementor-accordion-title{color:var( --e-global-color-accent );}.elementor-widget-accordion .elementor-active .elementor-accordion-icon svg{fill:var( --e-global-color-accent );}.elementor-widget-accordion .elementor-accordion-title{font-family:var( --e-global-typography-primary-font-family ), Sans-serif;font-weight:var( --e-global-typography-primary-font-weight );}.elementor-widget-accordion .elementor-tab-content{color:var( --e-global-color-text );font-family:var( --e-global-typography-text-font-family ), Sans-serif;font-weight:var( --e-global-typography-text-font-weight );}.elementor-3532 .elementor-element.elementor-element-2eaa174 .elementor-accordion-icon, .elementor-3532 .elementor-element.elementor-element-2eaa174 .elementor-accordion-title{color:var( --e-global-color-accent );}.elementor-3532 .elementor-element.elementor-element-2eaa174 .elementor-accordion-icon svg{fill:var( --e-global-color-accent );}.elementor-3532 .elementor-element.elementor-element-2eaa174 .elementor-active .elementor-accordion-icon, .elementor-3532 .elementor-element.elementor-element-2eaa174 .elementor-active .elementor-accordion-title{color:var( --e-global-color-primary );}.elementor-3532 .elementor-element.elementor-element-2eaa174 .elementor-active .elementor-accordion-icon svg{fill:var( --e-global-color-primary );}#featured-title{display:block;}#site-logo #site-logo-inner{max-width:140px !important;}#footer{display:block;}<\/style>\t\t<div data-elementor-type=\"section\" data-elementor-id=\"3532\" class=\"elementor elementor-3532\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e814fc2 e-flex e-con-boxed e-con e-parent\" data-id=\"e814fc2\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2eaa174 elementor-widget elementor-widget-accordion\" data-id=\"2eaa174\" data-element_type=\"widget\" data-widget_type=\"accordion.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-accordion\">\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-4891\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-4891\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Degree Information<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-4891\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-4891\"><p>This Masters programme aims to train postgraduate students in computational, mathematical and statistical methods to solve data-driven problems. The programme will create opportunities for students in the Computer Science, Statistics, Physics, Electrical Engineering or related fields to gain an interdisciplinary perspective on the emerging fields of Data Science.<\/p>\n<p>Students will register with their Home Institution but will attend coursework at Wits University in Johannesburg, Gauteng, in the first year. On completion of the coursework modules, students will move back to their Home Institutions for their second year of study.<\/p>\n<p><strong>Degree Information<\/strong><\/p>\n<p>The Masters programme extends over eighteen to twenty-four months of full-time study. The programme comprises compulsory and elective modules. Cross-disciplinary data-driven projects are offered both within the University and from a wide range of industry partners. A candidate must undertake modules to the value of 180 credits and must successfully complete the following courses to obtain a Master of Science by <i>Coursework and<\/i> <i>Research Report<\/i> in the field of e-Science.<\/p>\n<p><strong>Coursework Modules (Year 1 at Wits University)<\/strong><\/p>\n<p><strong>2 Compulsory Courses<\/strong><\/p>\n<ul>\n<li><em>Research Methods and Capstone Project in Data Science (15 credits)<\/em><br>This course gives the students the theoretical and practical skills to plan, conduct, analyse and present a scientific assignment (Capstone Project) in the area of Data Science by introducing them to research methodology, ethics and sustainability. The course is comprised of three parts: 1) scientific writing; 2) research methodology; and 3) scientific assignment. These three parts are integrated in a capstone project.<\/li>\n<li><em>Data Privacy and Ethics (15 credits)<\/em><br>This course introduces the students to the ethical and legal foundations of data science governance. The topics covered include technical processes of data collection, storage, exchange and access; ethical aspects of data management; legal and regulatory frameworks in South Africa and in relevant jurisdictions; data policy; data privacy; data ownership; legal liabilities of analytical decisions, and discrimination; algorithms and technical approaches to enhance data privacy; and relevant case studies.<\/li>\n<\/ul>\n<p><strong>Any 4 Elective Course on Offer<\/strong><\/p>\n<ul>\n<li><em>Adaptive Computation and Machine Learning (15 credits)<\/em><br>This course provides the candidate with an in\u2212depth understanding of adaptive computing and machine learning. The course consists of machine learning, pattern recognition and computational learning theory in artificial intelligence. Machine learning explores the study and construction of algorithms that can learn from and make predictions using data \u2013 such algorithms overcome the limitation of following strictly static program instructions by making data driven predictions or decisions, through building a model from sample inputs.<\/li>\n<li><em>Data Visualisation and Exploration (15 credits)<\/em><br>This course introduces the field of data visualisation which seeks to determine and present underlying correlated structures and relationships in data sets from a wide variety of application areas. The prime objective of the presentation is to communicate the information in a dataset so as to enhance understanding. The course is comprised of the following subjects: Data and image models; Visualisation attributes (colour) and design (layout); Exploratory data analysis; Interactive data visualisation; Multidimensional data; Graphical perception; Visualisation software (Python &amp; R); and Types of visualisation (Animation, Networks &amp; Text).<\/li>\n<li><em>Large Scale Computing Systems and Scientific Programming (15 credits)<\/em><br>Conducting e-research\/e-science requires a good understanding of the computing principles, methods and tools that have been developed to support the analysis of large-scale and complex data. The course focuses on the software stack but addresses hardware issues as necessary. The course covers a selection of following topics: Introduction to programming environments for scientific computing (e.g. Pandas, Numpy, matplotlib); Principles of distributed systems, and overview of parallel architectures and environments (e.g. FPGA, GPU, multi-core, cluster, grid); Large scale data transfer and storage; Frameworks for large scale data analysis (relational databases, map-reduce, streaming); Scientific workflow management: provenance and replication; Introduction to cloud computing and virtualisation; and Project (e.g. Programming large-data applications on open-source infrastructures for data processing and storage systems).<\/li>\n<li><em>Large Scale Optimisation for Data Science (15 credits)<\/em><br>Advanced areas of data science require a deeper understanding of the large scale discrete optimisation methods pertaining to the field. In order to bridge this mathematical gap and provide a foundation for further learning, this course will place more emphasis on topics such as convex optimisation, sub-gradient methods, localisation methods, decomposition and distributed optimisation, proximal and operator splitting methods, conjugate gradients, and nonconvex problems.<\/li>\n<li><em>Mathematical Foundations of Data Science (15 credits)<\/em><br>Advanced areas of data science require a deeper understanding of the fundamental mathematics pertaining to the field. In order to bridge this mathematical gap and provide a foundation for further learning, this course will place more emphasis on topics such as high-dimensional space, best-fit subspaces and singular value decomposition, random walks and Markov chains, statistical machine learning, clustering, random graphs, topic models, non-negative matrix factorisation, hidden Markov models, graphical models, wavelets, and sparse representations.<\/li>\n<li><em>Special Topics in Data Science (15 credits)<\/em><br>This module deals with specialised and applied concepts and trends in the domain specific areas of data sciences such as finance, health sciences, bioinformatics, natural sciences, social sciences, smart cities, education, and energy.<\/li>\n<li><em>Statistical Foundations of Data Science (15 credits)<\/em><br>This course provides an understanding of multivariate statistical methods. Hypothesis testing and confidence intervals. The ability to model data using well known statistical distributions as well as handle data that is both continuous and categorical. The ability to perform statistical modeling including multivariate regression and adjust for multiple hypothesis. Forecasting, extrapolation, prediction and modeling using statistical methods. Bayesian statistics. An understanding of bootstrapping and Monte Carlo simulation.<\/li>\n<\/ul>\n<p><em>** Not all electives are offered every year.<\/em><\/p>\n<p class=\"western\"><strong>Research Report (Year 2 at Home Institution)<\/strong><\/p>\n<ul>\n<li><em>Research Report: Data Science (90 credits)<\/em><br>The ability to do research is an essential skill for an individual pursuing a career in Data Science, and forms the basis for further post-graduate study. This module provides practical training for the development of research skills and bridges the gap between theory and practice, and established work and novel research. By working within established research structures in the Institution under the guidance of an expert, students will receive exposure to the methods, philosophy and ethos of research in the field of Data Science.<\/li>\n<\/ul><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-4892\" class=\"elementor-tab-title\" data-tab=\"2\" role=\"button\" aria-controls=\"elementor-tab-content-4892\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Entry requirements and Prerequisites<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-4892\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"region\" aria-labelledby=\"elementor-tab-title-4892\"><p><strong>Entry Requirements<\/strong><\/p><p>Applicants are required to have a Bachelor with Honours degree (NQF level 8 qualification) from a relevant discipline in Science or Engineering (Computer Science, Mathematics, Physics, and Statistics) OR a relevant NQF level 8 qualification or a relevant Professional Engineering Degree with demonstrable knowledge of basic principles of Computing, Calculus, Linear Algebra, Probability and Statistics. Applicants require a minimum of 65 percent in their NQF level 8 qualification and fulfill any additional institutional application requirements of the institution through which they are applying, and must be co-approved by the Consortium.<\/p><p>Applicants will also be required to complete a number of pre-requisite on-line courses.<\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t                    <\/div>\n\t\t        \n                    <div id=\"ma-tab\" class=\"clearfix eael-tab-content-item inactive\" data-title-link=\"ma-tab\">\n\t\t\t\t        <style>.elementor-3544 .elementor-element.elementor-element-5cfb6ca{--display:flex;--background-transition:0.3s;--padding-top:0px;--padding-bottom:0px;--padding-left:0px;--padding-right:0px;}.elementor-widget-accordion .elementor-accordion-icon, .elementor-widget-accordion .elementor-accordion-title{color:var( --e-global-color-primary );}.elementor-widget-accordion .elementor-accordion-icon svg{fill:var( --e-global-color-primary );}.elementor-widget-accordion .elementor-active .elementor-accordion-icon, .elementor-widget-accordion .elementor-active .elementor-accordion-title{color:var( --e-global-color-accent );}.elementor-widget-accordion .elementor-active .elementor-accordion-icon svg{fill:var( --e-global-color-accent );}.elementor-widget-accordion .elementor-accordion-title{font-family:var( --e-global-typography-primary-font-family ), Sans-serif;font-weight:var( --e-global-typography-primary-font-weight );}.elementor-widget-accordion .elementor-tab-content{color:var( --e-global-color-text );font-family:var( --e-global-typography-text-font-family ), Sans-serif;font-weight:var( --e-global-typography-text-font-weight );}.elementor-3544 .elementor-element.elementor-element-01a7b77 .elementor-accordion-icon, .elementor-3544 .elementor-element.elementor-element-01a7b77 .elementor-accordion-title{color:var( --e-global-color-accent );}.elementor-3544 .elementor-element.elementor-element-01a7b77 .elementor-accordion-icon svg{fill:var( --e-global-color-accent );}.elementor-3544 .elementor-element.elementor-element-01a7b77 .elementor-active .elementor-accordion-icon, .elementor-3544 .elementor-element.elementor-element-01a7b77 .elementor-active .elementor-accordion-title{color:var( --e-global-color-primary );}.elementor-3544 .elementor-element.elementor-element-01a7b77 .elementor-active .elementor-accordion-icon svg{fill:var( --e-global-color-primary );}#featured-title{display:block;}#site-logo #site-logo-inner{max-width:140px !important;}#footer{display:block;}<\/style>\t\t<div data-elementor-type=\"section\" data-elementor-id=\"3544\" class=\"elementor elementor-3544\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5cfb6ca e-flex e-con-boxed e-con e-parent\" data-id=\"5cfb6ca\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-01a7b77 elementor-widget elementor-widget-accordion\" data-id=\"01a7b77\" data-element_type=\"widget\" data-widget_type=\"accordion.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-accordion\">\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-1731\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-1731\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Degree Information<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1731\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-1731\"><p>This Masters programme aims to train postgraduate students in the use of statistical methods to conduct data-driven research in the social sciences and humanities. The programme will create opportunities for students in the social sciences and humanities to develop an interdisciplinary perspective on the emerging fields of Data Science.<\/p>\n<p>Students will register with their Home Institution but will attend coursework at Wits University in Johannesburg, Gauteng, in the first year. On completion of the coursework modules, students will move back to their Home Institutions for their second year of study.<\/p>\n<p><strong>Degree Information<\/strong><\/p>\n<p>The Masters programme extends over eighteen to twenty-four months of full-time study. The programme comprises compulsory and elective modules (with alternative MSc courses available by special permission to students who meet the prerequisites). Cross-disciplinary data-driven projects are offered both within the University and from a wide range of industry partners. A candidate must undertake modules to the value of 180 credits and must successfully complete the following courses to obtain a Master of Science by&nbsp;<em>Coursework and<\/em>&nbsp;<em>Research Report<\/em>&nbsp;in the field of e-Science.<\/p>\n<p><strong>Compulsory Coursework Modules (Year 1 at Wits University)<\/strong><\/p>\n<ul>\n<li><em>Research Methods and Capstone Project in Data Science (15 credits)<\/em><br>This course gives the students the theoretical and practical skills to plan, conduct, analyse and present a scientific assignment (Capstone Project) in the area of Data Science by introducing them to research methodology, ethics and sustainability. The course is comprised of three parts: 1) scientific writing; 2) research methodology; and 3) scientific assignment. These three parts are integrated in a capstone project.<\/li>\n<li><em>Data Privacy and Ethics (15 credits)<\/em><br>This course introduces the students to the ethical and legal foundations of data science governance. The topics covered include technical processes of data collection, storage, exchange and access; ethical aspects of data management; legal and regulatory frameworks in South Africa and in relevant jurisdictions; data policy; data privacy; data ownership; legal liabilities of analytical decisions, and discrimination; algorithms and technical approaches to enhance data privacy; and relevant case studies.<\/li>\n<li><em>Statistical Computing and Inference for the Social Sciences and Humanities (30 credits)<\/em><br>This course introduces statistical social research, with applications in the social sciences and humanities. It emphasises the development of practical skills for conducting quantitative research using statistical software.<\/li>\n<li><em>Statistical Modelling for the Social Sciences and Humanities (15 credits)*<\/em><br>This course focuses on statistical modelling methods applied in the social sciences and humanities. These include multiple regression models, generalised linear models, multilevel models, and structural equation models. It emphasises the ability to identify appropriate models based on the type of data and research objective, and to replicate and critically analyse applications in the students\u2019 substantive areas of expertise.<\/li>\n<li><em>Applied Data Science for the Social Sciences and Humanities (15 credits)<\/em><br>This course focuses on applying data science methods in the social sciences and humanities, including relevant programming skills. The emphasis is on practical applications, such as compiling and analysing textual and georeferenced data sets.<\/li>\n<li><em>Alternative MSc courses are available by special permission to students who meet the prerequisites.<\/em><\/li>\n<\/ul>\n<p><strong>Research Report (Year 2 at Home Institution)<\/strong><\/p>\n<ul>\n<li><em>Research Report: Data Science (90 credits)<\/em><br>The ability to do research is an essential skill for an individual pursuing a career in Data Science, and forms the basis for further post-graduate study. This module provides practical training for the development of research skills and bridges the gap between theory and practice, and established work and novel research. By working within established research structures in the Institution under the guidance of an expert, students will receive exposure to the methods, philosophy and ethos of research in the field of Data Science.<\/li>\n<\/ul>\n<p><strong>For information view the&nbsp;<em><a href=\"https:\/\/youtu.be\/JA8TlcDiI6I\">video<\/a><\/em>&nbsp;from the Seminar held on 23 September 2019.<\/strong><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-1732\" class=\"elementor-tab-title\" data-tab=\"2\" role=\"button\" aria-controls=\"elementor-tab-content-1732\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Entry requirements and Prerequisites<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1732\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"region\" aria-labelledby=\"elementor-tab-title-1732\"><p><strong>Entry Requirements<\/strong><\/p><p>Applicants are required to have a Bachelor\u2019s degree with Honours (NQF level 8 qualification) from a relevant discipline or field in the social sciences or humanities. Along with strong substantive knowledge in a relevant discipline or field, they must have a demonstrable knowledge of basic principles of quantitative social research (but need not have a previous specialisation in statistics or statistical computing). Applicants require a minimum of 65 percent in their NQF level 8 qualification to be considered, and they must fulfil any additional institutional application requirements of the institution through which they are applying, and must be co-approved by the Consortium.<\/p><p><strong>Prerequisite Courses for Master of Arts<\/strong><\/p><p>Applicants are required to have a Bachelor\u2019s degree with Honours (NQF level 8 qualification) from a relevant discipline or field in the social sciences or humanities. Along with strong substantive knowledge in a relevant discipline or field, they must have a demonstrable knowledge of basic principles of quantitative social research (but need not have a previous specialisation in statistics or statistical computing). Applicants require a minimum of 65 percent in their NQF level 8 qualification to be considered, and they must fulfil any additional institutional application requirements of the institution through which they are applying, and must be co-approved by the Consortium.<\/p><p>Although not compulsory, it is highly recommended that applicants complete the following courses:<\/p><ul><li>David M. Diez, Christopher D. Barr, Mine Cetinkaya-Rundel,\u00a0<strong><em>Introductory Statistics with Randomization and Simulation<\/em><\/strong>, chapter 1 (pp. 1-60), free download from<br \/><a href=\"https:\/\/www.openintro.org\/stat\/textbook.php?stat_book=isrs\">https:\/\/www.openintro.org\/stat\/textbook.php?stat_book=isrs<\/a><\/li><li><strong>R labs for the textbook<\/strong>, available at<br \/><a href=\"https:\/\/www.openintro.org\/book\/os\/\">https:\/\/www.openintro.org\/stat\/labs.php?stat_lab_software=R<\/a>:<ul><li>\u201cIntro to R and RStudio\u201d<\/li><li>\u201cIntroduction to Data\u201d<\/li><\/ul><\/li><li>Mine Cetinkaya-Rundel, \u201c<strong>Data Analysis and Statistical Inference<\/strong>\u201c, DataCamp Open Course (free but requires registration),<br \/><a href=\"https:\/\/www.datacamp.com\/community\/open-courses\/statistical-inference-and-data-analysis\">https:\/\/www.datacamp.com\/community\/open-courses\/statistical-inference-and-data-analysis<\/a><ul><li>\u201cIntroduction to R\u201d<\/li><li>\u201cIntroduction to data\u201d<\/li><\/ul><\/li><li>(Optional)<strong><em>\u00a0R Programming<\/em>\u00a0swirl lessons<\/strong>\u00a0(interactive, run in R\/RStudio):<ul><li>\u201cBasic building blocks\u201d<\/li><li>\u201cSequences of numbers\u201d<\/li><li>\u201cVectors\u201d<\/li><li>\u201cSubsetting vectors\u201d<\/li><\/ul><\/li><\/ul><p>For further information regarding the prerequisites, please send your enquiry to\u00a0<a href=\"mailto:e-science.research@wits.ac.za\">e-science.research@wits.ac.za<\/a><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t                    <\/div>\n\t\t        \n                    <div id=\"general-information-tab\" class=\"clearfix eael-tab-content-item inactive\" data-title-link=\"general-information-tab\">\n\t\t\t\t        <style>.elementor-3554 .elementor-element.elementor-element-2f97d2f{--display:flex;--background-transition:0.3s;--padding-top:0px;--padding-bottom:0px;--padding-left:0px;--padding-right:0px;}.elementor-widget-accordion .elementor-accordion-icon, .elementor-widget-accordion .elementor-accordion-title{color:var( --e-global-color-primary );}.elementor-widget-accordion .elementor-accordion-icon svg{fill:var( --e-global-color-primary );}.elementor-widget-accordion .elementor-active .elementor-accordion-icon, .elementor-widget-accordion .elementor-active .elementor-accordion-title{color:var( --e-global-color-accent );}.elementor-widget-accordion .elementor-active .elementor-accordion-icon svg{fill:var( --e-global-color-accent );}.elementor-widget-accordion .elementor-accordion-title{font-family:var( --e-global-typography-primary-font-family ), Sans-serif;font-weight:var( --e-global-typography-primary-font-weight );}.elementor-widget-accordion .elementor-tab-content{color:var( --e-global-color-text 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data-elementor-type=\"section\" data-elementor-id=\"3554\" class=\"elementor elementor-3554\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2f97d2f e-flex e-con-boxed e-con e-parent\" data-id=\"2f97d2f\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f4187f0 elementor-widget elementor-widget-accordion\" data-id=\"f4187f0\" data-element_type=\"widget\" data-widget_type=\"accordion.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-accordion\">\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2551\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-2551\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Funding<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2551\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-2551\"><p style=\"box-sizing: inherit; font-variant-ligatures: normal; font-variant-caps: normal; font-family: Roboto; font-size: 16px; font-style: normal; font-weight: 400; color: rgb(102, 102, 102);\">Currently, there is no further funding for either the MA or MSc in e-Science.<\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2552\" class=\"elementor-tab-title\" data-tab=\"2\" role=\"button\" aria-controls=\"elementor-tab-content-2552\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Applications<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2552\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"region\" aria-labelledby=\"elementor-tab-title-2552\"><p>Students are advised to apply as early as possible due to competition for places. For more information, see your Institution\u2019s application webpage.<\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2553\" class=\"elementor-tab-title\" data-tab=\"3\" role=\"button\" aria-controls=\"elementor-tab-content-2553\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><svg class=\"e-font-icon-svg e-fas-chevron-down\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><svg class=\"e-font-icon-svg e-fas-chevron-up\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M240.971 130.524l194.343 194.343c9.373 9.373 9.373 24.569 0 33.941l-22.667 22.667c-9.357 9.357-24.522 9.375-33.901.04L224 227.495 69.255 381.516c-9.379 9.335-24.544 9.317-33.901-.04l-22.667-22.667c-9.373-9.373-9.373-24.569 0-33.941L207.03 130.525c9.372-9.373 24.568-9.373 33.941-.001z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Careers<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2553\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"3\" role=\"region\" aria-labelledby=\"elementor-tab-title-2553\"><p><strong>MSc Careers<\/strong><\/p><p>Graduates of the programme can find data-oriented roles within academic institutions, technology, healthcare companies and the finance sector. Data scientist positions involve a wide range of responsibilities; such as conducting exploratory data analysis, applying statistical methodologies, deriving business insights from data, partnering with company executives, product and engineering teams to solve problems, identify trends and opportunities, inform, influence, support, and execute product decisions and launches.<\/p><p><strong>MA Careers<\/strong><\/p><p>Career opportunities vary depending on graduates\u2019 areas of specialisation in the social sciences or humanities, but they fall in two main categories.\u00a0 The first consists of newly emerging data-oriented research positions that explicitly target those with expertise in the social sciences and humanities \u2014 in academic institutions, social and policy research organisations (governmental and non-governmental), and the private sector (for example, in the legal, finance, health care, and technology industries).\u00a0 The second consists of positions that have traditionally targeted social science and humanities graduates, but in which data and computing expertise is increasingly valued as a complementary \u201cscarce skill.\u201d\u00a0 The competitive advantage of MA graduates is their unique ability to combine expertise in the social sciences or humanities with data-oriented research skills.<\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t                    <\/div>\n\t\t                    <\/div>\n        <\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Master&#8217;s Programmes MSc MA General Information Degree Information This Masters programme aims to train postgraduate students in computational, mathematical and statistical methods to solve data-driven problems. The programme will create opportunities for students in the Computer Science, Statistics, Physics, Electrical Engineering or related fields to gain an<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3332","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/pages\/3332","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/comments?post=3332"}],"version-history":[{"count":16,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/pages\/3332\/revisions"}],"predecessor-version":[{"id":4667,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/pages\/3332\/revisions\/4667"}],"wp:attachment":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/media?parent=3332"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}