{"course":{"productid":29818,"modality":3,"active":true,"language":"fr","title":"AWS Discovery Day: Machine Learning Basics","productcode":"AWSDD-MLB","vendorcode":"AW","vendorname":"Amazon Web Services","fullproductcode":"AW-AWSDD-MLB","courseware":{"has_ekit":true,"has_printkit":false,"language":""},"url":"https:\/\/portal.flane.ch\/course\/amazon-awsdd-mlb","objective":"<p>During this event, you will learn:<\/p>\n<ul>\n<li>What is Machine Learning?<\/li><li>What is the machine learning pipeline, and what are its phases?<\/li><li>What is the difference between supervised and unsupervised learning?<\/li><li>What is reinforcement learning?<\/li><li>What is deep learning?<\/li><\/ul>","audience":"<p>This event is intended for:<\/p>\n<ul>\n<li>Developers<\/li><li>Solution architects<\/li><li>Data engineers<\/li><li>Individuals interested in building solutions with machine learning - no machine learning experience required!<\/li><\/ul>","outline":"<h5>Section 1: Machine learning basics <\/h5><ul>\n<li>Classical programming vs. machine learning approach<\/li><li>What is a model?<\/li><li>Algorithm features, weights, and outputs<\/li><li>Machine learning algorithm categories<\/li><li>Supervised algorithms<\/li><li>Unsupervised algorithms<\/li><li>Reinforcement learning<\/li><\/ul><h5>Section 2: What is deep learning?<\/h5><ul>\n<li>How does deep learning work?<\/li><li>How deep learning is different<\/li><\/ul><h5>Section 3: The Machine Learning Pipeline<\/h5><ul>\n<li>Overview<\/li><li>Business problem<\/li><li>Data collection and integration<\/li><li>Data processing and visualization<\/li><li>Feature engineering<\/li><li>Model training and tuning<\/li><li>Model evaluation<\/li><li>Model deployment<\/li><\/ul><h5>Section 4: What are my next steps?<\/h5><ul>\n<li>Resources to continue learning<\/li><\/ul>","summary":"<p>Are you interested in machine learning, but not sure where to start? Join us for this session with an AWS expert and demystify the basics. Using real-world examples, you&rsquo;ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can unlock new insights and value for your business using machine learning.<\/p>\n<ul>\n<li>Level: Fundamental<\/li><li>Duration: 1.5 hours<\/li><\/ul><p>We recommend that attendees of this event continue learning with these:<\/p>\n<ul>\n<li>Courses\n<ul>\n<li><span class=\"attentionbbcode\" title=\"course: AW-AWSDL\">!<\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/amazon-mloe\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>MLOps Engineering on AWS <span class=\"fl-prod-pcode\">(MLOE)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/amazon-pdsasm\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Practical Data Science with Amazon SageMaker <span class=\"fl-prod-pcode\">(PDSASM)<\/span><\/a><\/span><\/li><li><span class=\"attentionbbcode\" title=\"course: AW-ML-PIPE\">!<\/span><\/li><\/ul><\/li><li>Resources\n<ul>\n<li>AWS Ramp-Up Guide: Machine Learning<\/li><\/ul><\/li><\/ul>","objective_plain":"During this event, you will learn:\n\n\n- What is Machine Learning?\n- What is the machine learning pipeline, and what are its phases?\n- What is the difference between supervised and unsupervised learning?\n- What is reinforcement learning?\n- What is deep learning?","audience_plain":"This event is intended for:\n\n\n- Developers\n- Solution architects\n- Data engineers\n- Individuals interested in building solutions with machine learning - no machine learning experience required!","outline_plain":"Section 1: Machine learning basics \n\n\n- Classical programming vs. machine learning approach\n- What is a model?\n- Algorithm features, weights, and outputs\n- Machine learning algorithm categories\n- Supervised algorithms\n- Unsupervised algorithms\n- Reinforcement learning\nSection 2: What is deep learning?\n\n\n- How does deep learning work?\n- How deep learning is different\nSection 3: The Machine Learning Pipeline\n\n\n- Overview\n- Business problem\n- Data collection and integration\n- Data processing and visualization\n- Feature engineering\n- Model training and tuning\n- Model evaluation\n- Model deployment\nSection 4: What are my next steps?\n\n\n- Resources to continue learning","summary_plain":"Are you interested in machine learning, but not sure where to start? Join us for this session with an AWS expert and demystify the basics. Using real-world examples, you\u2019ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can unlock new insights and value for your business using machine learning.\n\n\n- Level: Fundamental\n- Duration: 1.5 hours\nWe recommend that attendees of this event continue learning with these:\n\n\n- Courses\n\n- (!)\n- MLOps Engineering on AWS (MLOE)\n- Practical Data Science with Amazon SageMaker (PDSASM)\n- (!)\n- Resources\n\n- AWS Ramp-Up Guide: Machine Learning","version":"1.0","duration":{"unit":"d","value":0,"formatted":"2 heures"},"lastchanged":"2025-08-27T16:57:57+02:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course-schedule\/29818","source_lang":"fr","source":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course\/amazon-awsdd-mlb"}}