{"id":149,"date":"2022-03-25T11:03:03","date_gmt":"2022-03-25T11:03:03","guid":{"rendered":"https:\/\/felixaugenstein.com\/blog\/?p=149"},"modified":"2022-03-25T11:03:03","modified_gmt":"2022-03-25T11:03:03","slug":"accelerate-your-automation-data-ai-journey-build-your-first-machine-learning-model-and-get-started-with-data-science","status":"publish","type":"post","link":"https:\/\/felixaugenstein.com\/blog\/accelerate-your-automation-data-ai-journey-build-your-first-machine-learning-model-and-get-started-with-data-science\/","title":{"rendered":"Accelerate your Automation, Data &#038; AI Journey &#8211; Build your first Machine Learning model and get started with Data Science"},"content":{"rendered":"\n<ul class=\"wp-block-list\"><li>In this hands-on workshop we take a look behind the buzzwords: Machine Learning &amp; Data Science.\ud83c\udf93 <strong>What will you learn?\u00a0<\/strong><ul><li>The difference between AI and ML<\/li><li>The different types of Machine Learning<\/li><li>How to structure Data Science projects<\/li><\/ul><\/li><li>We will develop a Machine Learning model to predict customer churn with an AutoAI feature &#8211; to build Machine Learning models automatically &#8211; as well as Jupyter Notebooks. For this hands-on session we will be using the Cloud Pak for Data as a Service on the IBM Cloud.<\/li><\/ul>\n\n\n\n<p>You can access the session here:<\/p>\n\n\n\n<p><a href=\"https:\/\/www.crowdcast.io\/e\/auto-data-ai\/1\">https:\/\/www.crowdcast.io\/e\/auto-data-ai\/1<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this hands-on workshop we take a look behind the buzzwords: Machine Learning &amp; Data Science.\ud83c\udf93 What will you learn?\u00a0 The difference between AI and ML The different types of Machine Learning How to structure Data Science projects We will develop a Machine Learning model to predict customer churn with [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":151,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[24,21,22,4,26,27,25,20],"tags":[],"class_list":["post-149","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-autoai","category-cloud-pak-for-data","category-cognos","category-ibm-watson","category-jupyter-notebook","category-python","category-spss-modeler","category-watson-studio"],"_links":{"self":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/149","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/comments?post=149"}],"version-history":[{"count":1,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/149\/revisions"}],"predecessor-version":[{"id":152,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/posts\/149\/revisions\/152"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/media\/151"}],"wp:attachment":[{"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/media?parent=149"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/categories?post=149"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/felixaugenstein.com\/blog\/wp-json\/wp\/v2\/tags?post=149"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}