Concepts of big data analysis, meaning, significance, and analysis of educational data; identifying relationships (association) clustering; classification of data (classification) analysis of various types of data, text, time series, pictures; various tools for big data analysis; data preparation for analysis; programs for large data analysis; the use of techniques such as Decision Tree; Na?ve Bayes; SVM in large-scale analysis; data display in various formats in data analysis program; studying educational research literature to design big data analysis to solve problems and to increase education efficiency
หมายเหตุ เรียน C = Lecture L = Lab R = ประชุม S = Self Study T = ติว หมวด B = วิชาเสริมพื้นฐาน E = วิชาเลือกเฉพาะสาขา F = วิชาเลือกเสรี G = วิชาศึกษาทั่วไป M = วิชาพื้นฐาน W = วิชาบังคับ X = - ยังไม่กำหนด
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