{"course":{"productid":19997,"modality":6,"active":true,"language":"fr","title":"IBM SPSS Modeler Foundations (V18.2)","productcode":"0A069G","vendorcode":"IB","vendorname":"IBM","fullproductcode":"IB-0A069G","courseware":{"has_ekit":true,"has_printkit":false,"language":"en"},"url":"https:\/\/portal.flane.ch\/course\/ibm-0a069g","essentials":"<ul>\n\n\t<li>Knowledge of your business requirements<\/li><\/ul>","audience":"<ul>\n\n\t<li>Data scientists<\/li><li>Business analysts<\/li><li>Clients who are new to IBM SPSS Modeler or want to find out more about using it<\/li><\/ul>","contents":"<p>Introduction to IBM SPSS Modeler\n<\/p>\n<ul>\n<li>&bull; Introduction to data science<\/li><li>&bull; Describe the CRISP-DM methodology<\/li><li>&bull; Introduction to IBM SPSS Modeler<\/li><li>&bull; Build models and apply them to new data<\/li><\/ul><p>\nCollect initial data\n<\/p>\n<ul>\n<li>&bull; Describe field storage<\/li><li>&bull; Describe field measurement level<\/li><li>&bull; Import from various data formats<\/li><li>&bull; Export to various data formats<\/li><\/ul><p>\nUnderstand the data\n<\/p>\n<ul>\n<li>&bull; Audit the data<\/li><li>&bull; Check for invalid values<\/li><li>&bull; Take action for invalid values<\/li><li>&bull; Define blanks<\/li><\/ul><p>\nSet the unit of analysis\n<\/p>\n<ul>\n<li>&bull; Remove duplicates<\/li><li>&bull; Aggregate data<\/li><li>&bull; Transform nominal fields into flags<\/li><li>&bull; Restructure data<\/li><\/ul><p>\nIntegrate data\n<\/p>\n<ul>\n<li>&bull; Append datasets<\/li><li>&bull; Merge datasets<\/li><li>&bull; Sample records<\/li><\/ul><p>\nTransform fields\n<\/p>\n<ul>\n<li>&bull; Use the Control Language for Expression Manipulation<\/li><li>&bull; Derive fields<\/li><li>&bull; Reclassify fields<\/li><li>&bull; Bin fields<\/li><\/ul><p>\nFurther field transformations\n<\/p>\n<ul>\n<li>&bull; Use functions<\/li><li>&bull; Replace field values<\/li><li>&bull; Transform distributions<\/li><\/ul><p>\nExamine relationships\n<\/p>\n<ul>\n<li>&bull; Examine the relationship between two categorical fields<\/li><li>&bull; Examine the relationship between a categorical&nbsp; and continuous field<\/li><li>&bull; Examine the relationship between two continuous fields<\/li><\/ul><p>\nIntroduction to modeling\n<\/p>\n<ul>\n<li>&bull; Describe modeling objectives<\/li><li>&bull; Create supervised models<\/li><li>&bull; Create segmentation models<\/li><\/ul><p>\nImprove efficiency\n<\/p>\n<ul>\n<li>&bull; Use database scalability by SQL pushback<\/li><li>&bull; Process outliers and missing values with the Data Audit node<\/li><li>&bull; Use the Set Globals node<\/li><li>&bull; Use parameters<\/li><li>&bull; Use looping and conditional execution<\/li><\/ul>","outline":"<p>Introduction to IBM SPSS Modeler\n<\/p>\n<ul>\n<li>&bull; Introduction to data science<\/li><li>&bull; Describe the CRISP-DM methodology<\/li><li>&bull; Introduction to IBM SPSS Modeler<\/li><li>&bull; Build models and apply them to new data<\/li><\/ul><p>\nCollect initial data\n<\/p>\n<ul>\n<li>&bull; Describe field storage<\/li><li>&bull; Describe field measurement level<\/li><li>&bull; Import from various data formats<\/li><li>&bull; Export to various data formats<\/li><\/ul><p>\nUnderstand the data\n<\/p>\n<ul>\n<li>&bull; Audit the data<\/li><li>&bull; Check for invalid values<\/li><li>&bull; Take action for invalid values<\/li><li>&bull; Define blanks<\/li><\/ul><p>\nSet the unit of analysis\n<\/p>\n<ul>\n<li>&bull; Remove duplicates<\/li><li>&bull; Aggregate data<\/li><li>&bull; Transform nominal fields into flags<\/li><li>&bull; Restructure data<\/li><\/ul><p>\nIntegrate data\n<\/p>\n<ul>\n<li>&bull; Append datasets<\/li><li>&bull; Merge datasets<\/li><li>&bull; Sample records<\/li><\/ul><p>\nTransform fields\n<\/p>\n<ul>\n<li>&bull; Use the Control Language for Expression Manipulation<\/li><li>&bull; Derive fields<\/li><li>&bull; Reclassify fields<\/li><li>&bull; Bin fields<\/li><\/ul><p>\nFurther field transformations\n<\/p>\n<ul>\n<li>&bull; Use functions<\/li><li>&bull; Replace field values<\/li><li>&bull; Transform distributions<\/li><\/ul><p>\nExamine relationships\n<\/p>\n<ul>\n<li>&bull; Examine the relationship between two categorical fields<\/li><li>&bull; Examine the relationship between a categorical&nbsp; and continuous field<\/li><li>&bull; Examine the relationship between two continuous fields<\/li><\/ul><p>\nIntroduction to modeling\n<\/p>\n<ul>\n<li>&bull; Describe modeling objectives<\/li><li>&bull; Create supervised models<\/li><li>&bull; Create segmentation models<\/li><\/ul><p>\nImprove efficiency\n<\/p>\n<ul>\n<li>&bull; Use database scalability by SQL pushback<\/li><li>&bull; Process outliers and missing values with the Data Audit node<\/li><li>&bull; Use the Set Globals node<\/li><li>&bull; Use parameters<\/li><li>&bull; Use looping and conditional execution<\/li><\/ul>","summary":"<p>This course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.<\/p>","essentials_plain":"- Knowledge of your business requirements","audience_plain":"- Data scientists\n- Business analysts\n- Clients who are new to IBM SPSS Modeler or want to find out more about using it","contents_plain":"Introduction to IBM SPSS Modeler\n\n\n\n- \u2022 Introduction to data science\n- \u2022 Describe the CRISP-DM methodology\n- \u2022 Introduction to IBM SPSS Modeler\n- \u2022 Build models and apply them to new data\n\nCollect initial data\n\n\n\n- \u2022 Describe field storage\n- \u2022 Describe field measurement level\n- \u2022 Import from various data formats\n- \u2022 Export to various data formats\n\nUnderstand the data\n\n\n\n- \u2022 Audit the data\n- \u2022 Check for invalid values\n- \u2022 Take action for invalid values\n- \u2022 Define blanks\n\nSet the unit of analysis\n\n\n\n- \u2022 Remove duplicates\n- \u2022 Aggregate data\n- \u2022 Transform nominal fields into flags\n- \u2022 Restructure data\n\nIntegrate data\n\n\n\n- \u2022 Append datasets\n- \u2022 Merge datasets\n- \u2022 Sample records\n\nTransform fields\n\n\n\n- \u2022 Use the Control Language for Expression Manipulation\n- \u2022 Derive fields\n- \u2022 Reclassify fields\n- \u2022 Bin fields\n\nFurther field transformations\n\n\n\n- \u2022 Use functions\n- \u2022 Replace field values\n- \u2022 Transform distributions\n\nExamine relationships\n\n\n\n- \u2022 Examine the relationship between two categorical fields\n- \u2022 Examine the relationship between a categorical\u00a0 and continuous field\n- \u2022 Examine the relationship between two continuous fields\n\nIntroduction to modeling\n\n\n\n- \u2022 Describe modeling objectives\n- \u2022 Create supervised models\n- \u2022 Create segmentation models\n\nImprove efficiency\n\n\n\n- \u2022 Use database scalability by SQL pushback\n- \u2022 Process outliers and missing values with the Data Audit node\n- \u2022 Use the Set Globals node\n- \u2022 Use parameters\n- \u2022 Use looping and conditional execution","outline_plain":"Introduction to IBM SPSS Modeler\n\n\n\n- \u2022 Introduction to data science\n- \u2022 Describe the CRISP-DM methodology\n- \u2022 Introduction to IBM SPSS Modeler\n- \u2022 Build models and apply them to new data\n\nCollect initial data\n\n\n\n- \u2022 Describe field storage\n- \u2022 Describe field measurement level\n- \u2022 Import from various data formats\n- \u2022 Export to various data formats\n\nUnderstand the data\n\n\n\n- \u2022 Audit the data\n- \u2022 Check for invalid values\n- \u2022 Take action for invalid values\n- \u2022 Define blanks\n\nSet the unit of analysis\n\n\n\n- \u2022 Remove duplicates\n- \u2022 Aggregate data\n- \u2022 Transform nominal fields into flags\n- \u2022 Restructure data\n\nIntegrate data\n\n\n\n- \u2022 Append datasets\n- \u2022 Merge datasets\n- \u2022 Sample records\n\nTransform fields\n\n\n\n- \u2022 Use the Control Language for Expression Manipulation\n- \u2022 Derive fields\n- \u2022 Reclassify fields\n- \u2022 Bin fields\n\nFurther field transformations\n\n\n\n- \u2022 Use functions\n- \u2022 Replace field values\n- \u2022 Transform distributions\n\nExamine relationships\n\n\n\n- \u2022 Examine the relationship between two categorical fields\n- \u2022 Examine the relationship between a categorical\u00a0 and continuous field\n- \u2022 Examine the relationship between two continuous fields\n\nIntroduction to modeling\n\n\n\n- \u2022 Describe modeling objectives\n- \u2022 Create supervised models\n- \u2022 Create segmentation models\n\nImprove efficiency\n\n\n\n- \u2022 Use database scalability by SQL pushback\n- \u2022 Process outliers and missing values with the Data Audit node\n- \u2022 Use the Set Globals node\n- \u2022 Use parameters\n- \u2022 Use looping and conditional execution","summary_plain":"This course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.","skill_level":"Beginner","version":"1","duration":{"unit":"d","value":2,"formatted":"2 jours"},"pricelist":{"List Price":{"FR":{"country":"FR","currency":"EUR","taxrate":19.6,"price":1500},"CH":{"country":"CH","currency":"CHF","taxrate":8.1,"price":1890}}},"lastchanged":"2025-07-29T12:17:56+02:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course-schedule\/19997","source_lang":"fr","source":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course\/ibm-0a069g"}}