{"@id":"https://credentialengineregistry.org/resources/ce-f75786f4-61b3-4fe9-b8dd-92013b4f9a69","@type":"ceterms:OpenBadge","@context":"https://credreg.net/ctdl/schema/context/json","ceterms:ctid":"ce-f75786f4-61b3-4fe9-b8dd-92013b4f9a69","ceterms:name":{"en-US":"WGU Certificate: Data Analytics Fundamentals"},"ceterms:image":"https://api.badgr.io/public/badges/cVYdt-IORtWIDynMWGP6Kw/image","ceterms:ownedBy":["https://credentialengineregistry.org/resources/ce-036d082d-d80e-41a7-99a0-2d63a4ad3a4a"],"ceterms:requires":[{"@type":"ceterms:ConditionProfile","ceterms:name":{"en-US":"Open Badges Criteria"},"ceterms:assertedBy":["https://credentialengineregistry.org/resources/ce-036d082d-d80e-41a7-99a0-2d63a4ad3a4a"],"ceterms:description":{"en-US":"Credential Detail\n\nRecipients of WGU’s Data Analytics Fundamentals Certificate have demonstrated competence in the following areas via rigorous assessment activities completed through Western Governors University:\n\nExploratory Data Analysis\n\nThe learner interprets central tendency, correlations, and variation to inform organizational decisions. \nThe learner conducts parametric hypothesis testing.\n\nPredictive Modeling\n\nThe learner employs logistic regression algorithms in describing phenomena.\nThe learner employs multiple regression algorithms with categorical and numerical predictors in describing phenomena.\nThe learner makes assertions based on regression modeling.\n\nData Mining I\n\nThe learner applies observations to appropriate classes and categories using classification models.\nThe learner implements prediction data mining models to find hard-to-spot relationships among variables.\nThe learner evaluates data mining model performance for precision, accuracy, and model comparison.\n\nRepresentation and Reporting\n\nThe learner communicates data insights to technical and nontechnical audiences.\nThe learner creates?data representations?to offer insight into an organizational problem.?\nThe learner?designs?interactive dashboards to support executive decision-making.\n\n? \n\nCompetency Demonstration Highlights\n\nRecipients of this credential complete the following tasks and deliverables as part of their assessment activities:\n\nIdentifies distribution functions for continuous and categorical variables.\nUses statistical techniques to perform hypothesis testing on continuous and categorical data.\nSelects and justifies a particular regression modeling approach.\nCreates a regression model using programmatic approaches.\nUses a regression model to answer a specific business question.\nCreates a supervised machine learning model using programmatic approaches.\nSelects and justifies a particular supervised machine learning model to address a business question.\nTrains a supervised machine learning model using training and validation data sets.\nAdjusts data presentation to fit a specific audience.\nCreates data reports to identify actionable insights.\nCreates dashboards to present analytics results to stakeholders.\n\nWGU Accreditation\n\nWGU is regionally accredited by the Northwest Commission on Colleges and Universities. The WGU Teachers College is granted accreditation at the initial-licensure level from the Council for the Accreditation of Educator Preparation (CAEP). WGU nursing degree programs are accredited by the Commission for Collegiate Nursing Education (CCNE). The Health Informatics program is accredited by the Commission of Accreditation for Health Informatics and Information Management Education (CAHIIM). The WGU Business College is accredited by the Accreditation Council for Business Schools and Programs (ACBSP)."}},{"@type":"ceterms:ConditionProfile","ceterms:name":{"en-US":"WGU Certificate: Data Analytics Fundamentals v1.5"},"ceterms:assertedBy":["https://credentialengineregistry.org/resources/ce-036d082d-d80e-41a7-99a0-2d63a4ad3a4a"],"ceterms:description":{"en-US":"The indicated courses must be satisfied in order for a student to earn the credential. A student must be enrolled in a program and catalog version where the credential is embedded. 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