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Measures of variability; range, variance, standard deviation

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Data analysis techniques; filtering, grouping, sorting

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Common pitfalls and biases in data analysis

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Probability and Statistics

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Basic probability concepts; events, probability measures, conditional probability

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Statistical inference; hypothesis testing, confidence intervals

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Supervised and unsupervised learning; classification, regression, clustering

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Principles of effective data communication

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Presenting data insights to stakeholders

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Spreadsheets; Excel, Google Sheets

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Big Data and NoSQL Databases

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Introduction to big data and NoSQL databases

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