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Hadoop, Spark, and distributed computing

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NoSQL databases; MongoDB, Cassandra, Redis

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Data cleaning and preprocessing

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Introduction to time series analysis

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Time series decomposition; trend, seasonality, residuals

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Forecasting; ARIMA, exponential smoothing

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Geospatial Data Analysis

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Introduction to geospatial data analysis

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Geospatial data types; points, polygons, rasters

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Geospatial analysis; spatial autocorrelation, spatial regression

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Real-world applications of data literacy; business, healthcare, social sciences

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Data-driven decision making; challenges, opportunities

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