{"id":6839,"date":"2022-04-28T20:48:16","date_gmt":"2022-04-28T20:48:16","guid":{"rendered":"https:\/\/www.tun.com\/courses\/2019\/12\/23\/ai-workflow-feature-engineering-and-bias-detection\/"},"modified":"2022-04-28T20:48:17","modified_gmt":"2022-04-28T20:48:17","slug":"ai-workflow-feature-engineering-and-bias-detection","status":"publish","type":"post","link":"https:\/\/www.tun.com\/courses\/ai-workflow-feature-engineering-and-bias-detection\/ibm\/","title":{"rendered":"AI Workflow: Feature Engineering and Bias Detection"},"content":{"rendered":"
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Description<\/h2>\n

This is the third course in the IBM AI Enterprise Workflow Certification specialization.\u00a0\u00a0\u00a0 You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.\u00a0\u00a0<\/p>\n

Course 3 introduces you to the next stage of the workflow for our hypothetical media company.\u00a0 In this stage of work you will learn best practices for feature engineering, handling class imbalances and detecting bias in the data.\u00a0 Class imbalances can seriously affect the validity of your machine learning models, and the mitigation of bias in data is essential to reducing the risk associated with biased models.\u00a0 These topics will be followed by sections on best practices for dimension reduction, outlier detection, and unsupervised learning techniques for finding patterns in your data.\u00a0 The case studies will focus on topic modeling and data visualization.
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\nBy the end of this course you will be able to:
\n1.\u00a0 Employ the tools that help address class and class imbalance issues
\n2.\u00a0 Explain the ethical considerations regarding bias in data
\n3.\u00a0 Employ ai Fairness 360 open source libraries to detect bias in models
\n4.\u00a0 Employ dimension reduction techniques for both EDA and transformations stages
\n5.\u00a0 Describe topic modeling techniques in natural language processing
\n6.\u00a0 Use topic modeling and visualization to explore text data
\n7.\u00a0 Employ outlier handling best practices in high dimension data
\n8.\u00a0 Employ outlier detection algorithms as a quality assurance tool and a modeling tool
\n9.\u00a0 Employ unsupervised learning techniques using pipelines as part of the AI workflow
\n10.\u00a0 Employ basic clustering algorithms
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\nWho should take this course?
\nThis course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this course is NOT for you as you need real world expertise to benefit from the content of these courses.
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\nWhat skills should you have?
\nIt is assumed that you have completed Courses 1 and 2 of the IBM AI Enterprise Workflow specialization and you have a solid understanding of the following topics prior to starting this course: Fundamental understanding of Linear Algebra; Understand sampling, probability theory, and probability distributions; Knowledge of descriptive and inferential statistical concepts; General understanding of machine learning techniques and best practices; Practiced understanding of Python and the packages commonly used in data science: NumPy, Pandas, matplotlib, scikit-learn; Familiarity with IBM Watson Studio; Familiarity with the design thinking process.<\/p>\n

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Price: Enroll For Free!<\/h2>\n
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View Class<\/a><\/div>\n
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Language:<\/strong> <\/em>English<\/p>\n<\/div>\n

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Subtitles<\/strong>: <\/em>English<\/p>\n<\/div>\n<\/div>\n

AI Workflow: Feature Engineering and Bias Detection – IBM<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Description This is the third course in the IBM AI Enterprise Workflow Certification specialization.\u00a0\u00a0\u00a0 You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.\u00a0\u00a0 Course 3 introduces you to the next stage of the workflow […]<\/p>\n","protected":false},"author":1,"featured_media":19489,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[41],"tags":[],"class_list":["post-6839","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ibm"],"aioseo_notices":[],"uagb_featured_image_src":{"full":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"thumbnail":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education-150x150.png",150,150,true],"medium":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education-300x180.png",300,180,true],"medium_large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"1536x1536":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"2048x2048":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false]},"uagb_author_info":{"display_name":"Axiom Pegasus","author_link":"https:\/\/www.tun.com\/courses\/author\/magic\/"},"uagb_comment_info":0,"uagb_excerpt":"Description This is the third course in the IBM AI Enterprise Workflow Certification specialization.\u00a0\u00a0\u00a0 You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.\u00a0\u00a0 Course 3 introduces you to the next stage of the workflow…","featured_media_src_url":"https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png","_links":{"self":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/6839","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/comments?post=6839"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/6839\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media\/19489"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media?parent=6839"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/categories?post=6839"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/tags?post=6839"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}