Global Certificate in Data Cleaning for Connected Learning
-- ViewingNowThe Global Certificate in Data Cleaning for Connected Learning is a comprehensive course designed to equip learners with essential data cleaning skills in high demand across industries. Data cleaning, also known as data cleansing or data scrubbing, is the process of identifying and correcting or removing errors, inaccuracies, and inconsistencies in datasets to improve their quality and reliability.
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⢠Unit 1: Introduction to Data Cleaning â fundamental concepts, importance, and best practices. ⢠Unit 2: Data Quality Assessment â measuring data quality, identifying issues, and setting standards. ⢠Unit 3: Data Preprocessing Techniques â handling missing data, outliers, and inconsistent values. ⢠Unit 4: Data Integration & Harmonization â merging, matching, and aligning disparate datasets. ⢠Unit 5: Data Transformation & Normalization â reshaping, encoding, and scaling variables. ⢠Unit 6: Data Validation & Verification â checking data accuracy, consistency, and compliance. ⢠Unit 7: Data Cleaning Tools & Software â exploring popular tools, libraries, and platforms. ⢠Unit 8: Data Cleaning Case Studies â real-world examples and applications. ⢠Unit 9: Data Governance & Management â establishing policies, procedures, and strategies. ⢠Unit 10: Data Cleaning Ethics & Privacy â addressing confidentiality, security, and ethical concerns.
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