{"@id":"https://credentialengineregistry.org/resources/ce-bbb2fb03-f1b9-4815-b66a-5e61a0162d6c","@type":"ceterms:MicroCredential","@context":"https://credreg.net/ctdl/schema/context/json","ceterms:ctid":"ce-bbb2fb03-f1b9-4815-b66a-5e61a0162d6c","ceterms:name":{"en-US":"JPMorgan Chase Data Analyst Micro-credential"},"ceterms:image":"https://api.badgr.io/public/badges/zSgSNQJnRzCsY9lWA-klKw/image","ceterms:keyword":{"en-US":["Data Analysis","Database Management","Partnership Series Micro-Credentials","Statistics"]},"ceterms:ownedBy":["https://credentialengineregistry.org/resources/ce-886e0dba-db0a-40f9-9067-1b282853d3fd"],"ceterms:requires":[{"@type":"ceterms:ConditionProfile","ceterms:name":{"en-US":"Open Badges Criteria"},"ceterms:description":{"en-US":"IT153: Spreadsheet Applications\nThis course examines spreadsheet concepts including calculations, formulas, built-in functions, and spreadsheet design. Earners create spreadsheets and manipulate data to solve business problems. The course further explores topics such as charts, data tables, pivot tables, and what-if analysis.\n\nIT234: Database Concepts\nThis course prepares earners learn database programming. Earners are exposed to more advanced concepts of database management systems and SQL programming language. This course provides earners with the business context in which data is used and how it is transformed into information. Earners identify the information needs and general usage of data within the modern business context and link the use of relational database management systems to data needs.\n\nIN300: Programming for Data Analysis (Python, R, and Java)\nThis course examines the use of Python, R, and Java to analyze data of all types. Fundamental programming concepts are covered for each language. These include data types, variables, introduction to regular expressions, decisions, iteration, and introduction to collections using arrays, lists, and key-value pairs. The importance of securing data is stressed throughout the course.\n\nIN302: Reporting and Visualization\nThis course focuses on how to prepare the collected and analyzed data for decision-making through the use of appropriate reporting formats including graphs, charts, diagrams, and so forth. Industry-wide data reporting and visualization tools are examined and evaluated.\n\nIT350: Advanced Database Concepts\nThis course incorporates advanced concepts of the database language Transact-SQL (T-SQL) for creating efficient database implementations. It focuses on the use of T-SQL programming language and connect to an MS SQL Server database for displaying organized information to users. You will explore the various fundamental features of the T-SQL language such as DataTypes, Sets, and Builtin functions. Earners explore the programmability of SQL by creating stored procedures; learn how to format a result set by sorting, filtering, and grouping; apply advanced SQL query techniques such as subqueries and common table expressions; use Report Builder to generate analytical reports from your data; and examine the use of non-SQL relational databases.\n\nIN401: Data Curation Concepts\nThis course examines the topic of data curation and the role of the data curator. Topics include extraction, transformation, and loading (ETL) of data from one source to another, and the integration, ingestion, and fusion of multiple sets of data from the perspective of the data curator.\n\nIN402: Modeling and Predictive Analysis\nThis course discusses modeling techniques for both relational and nonrelational databases. Techniques for modeling, including conceptual, logical, and physical designs, along with entity-relationship diagrams (ERD), are examined and used to better understand current data so as to improve performance to provide competitive advantage. Regression techniques, machine learning, and other tools are used to examine data and conduct predictive analysis.\n\nMM207: Statistics\nThis course serves as an introduction to collecting, organizing and summarizing, and analyzing data using statistical software. Topics include basic terminology, measurement, sampling procedures, graphical and numerical descriptions of data, basic probability, and making inferences from a sample to the population. Statistical software is required in this course and used extensively. The course focuses on \"thinking with\" statistics rather than \"computing\" statistics.\n\nSS290: Data in Our World - Introduction to Data Literacy\nData literacy is the ability to critically understand and evaluate information obtained from data. In today's information-driven world, our society is inundated with data. Yet, a robust math background is not required in order to become cognizant and adept with data literacy."},"ceterms:subjectWebpage":"https://catalog.purdueglobal.edu/bulletin/jpmorgan-chase-data-analyst/"}],"ceterms:offeredBy":["https://credentialengineregistry.org/resources/ce-886e0dba-db0a-40f9-9067-1b282853d3fd"],"ceterms:inLanguage":["en-US"],"ceterms:description":{"en-US":"Individuals completing the JPMorgan Chase Data Analyst Micro-credential develop skills associated with a variety of quantitative analysis and reporting tools. The required courses advance learners' understanding in critical areas such as database structure, programming for data analysis, predictive modeling, and effective reporting of data."},"ceterms:credentialId":"https://api.badgr.io/public/badges/zSgSNQJnRzCsY9lWA-klKw","ceterms:dateEffective":"2024-02-15","ceterms:subjectWebpage":"https://catalog.purdueglobal.edu/bulletin/jpmorgan-chase-data-analyst/","ceterms:credentialStatusType":{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://credreg.net/ctdl/terms/CredentialStatus","ceterms:targetNode":"credentialStat:Active","ceterms:frameworkName":{"en-US":"Credential Status"},"ceterms:targetNodeName":{"en-US":"Active"},"ceterms:targetNodeDescription":{"en-US":"Awards of the credential are ongoing."}},"ceterms:usesVerificationService":["https://credentialengineregistry.org/resources/ce-7b8a3dcf-938e-4896-993f-545d245908b9"]}