{"id":6822,"date":"2022-04-28T20:48:09","date_gmt":"2022-04-28T20:48:09","guid":{"rendered":"https:\/\/www.tun.com\/courses\/2019\/12\/23\/ai-workflow-data-analysis-and-hypothesis-testing\/"},"modified":"2022-04-28T20:48:09","modified_gmt":"2022-04-28T20:48:09","slug":"ai-workflow-data-analysis-and-hypothesis-testing","status":"publish","type":"post","link":"https:\/\/www.tun.com\/courses\/ai-workflow-data-analysis-and-hypothesis-testing\/ibm\/","title":{"rendered":"AI Workflow: Data Analysis and Hypothesis Testing"},"content":{"rendered":"
\n
\n
\n

Description<\/h2>\n

This is the second course in the IBM AI Enterprise Workflow Certification specialization.\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

In this course you will begin your work for a hypothetical streaming media company by doing exploratory data analysis (EDA).\u00a0 Best practices for data visualization, handling missing data, and hypothesis testing will be introduced to you as part of your work.\u00a0 You will learn techniques of estimation with probability distributions and extending these estimates to apply null hypothesis significance tests. You will apply what you learn through two hands on case studies: data visualization and multiple testing using a simple pipeline.
\n\u00a0
\nBy the end of this course you should be able to:
\n1.\u00a0 List several best practices concerning EDA and data visualization
\n2.\u00a0 Create a simple dashboard in Watson Studio
\n3.\u00a0 Describe strategies for dealing with missing data
\n4.\u00a0 Explain the difference between imputation and multiple imputation
\n5.\u00a0 Employ common distributions to answer questions about event probabilities
\n6.\u00a0 Explain the investigative role of hypothesis testing in EDA
\n7.\u00a0 Apply several methods for dealing with multiple testing
\n\u00a0
\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.<\/p>\n

What skills should you have?
\nIt is assumed that you have completed Course 1 of the IBM AI Enterprise Workflow specialization and 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

<\/div>\n

Price: Enroll For Free!<\/h2>\n
<\/div>\n
View Class<\/a><\/div>\n
<\/div>\n
\n
\n

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

\n

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

AI Workflow: Data Analysis and Hypothesis Testing – IBM<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Description This is the second course in the IBM AI Enterprise Workflow Certification specialization.\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 In this course you will begin your work for a hypothetical […]<\/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-6822","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 second course in the IBM AI Enterprise Workflow Certification specialization.\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 In this course you will begin your work for a hypothetical…","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\/6822","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=6822"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/6822\/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=6822"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/categories?post=6822"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/tags?post=6822"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}