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第1回
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Descriptive Statistics
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Learn and apply measures of central tendency and dispersion.
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第2回
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DescriptiveStatistics
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Learn and apply correlations, linkages, and cross tabulation tables.
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第3回
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Probability
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Learn and apply probability distribution, normal distribution, binomial distribution, and standardization of data.
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第4回
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Estimated Statistics
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Learn and apply estimators.
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第5回
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Interval Estimation
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Learn and apply interval estimation.
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第6回
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Test of the Difference of Proportions
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Learn and apply χ2 Test.
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第7回
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Test of the Mean Difference
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Learn and apply t-tests.
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第8回
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Bayesian Statistics
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Learn and apply the fundamentals of Bayesian statistics. The course also covers the concept of statistical power.
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第9回
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Introduction to Machine Learning
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Learn and apply sorting and algorithms, cloud services and big data, types of machine learning.
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第10回
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Supervised Machine Learning
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Learn and apply regression analysis (single regression, multiple regression, polynomial regression).
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第11回
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Supervised Machine Learning
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Learn and apply various classification algorithms, including Logistic Regression and k-Nearest Neighbors (k-NN). This section also covers model evaluation, including techniques for data splitting and the use of different evaluation metrics.
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第12回
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Supervised Machine Learning
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Learn and apply various classification algorithms, including SVM, decision trees, random forests).
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第13回
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Unsupervised Machine Learning
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Learn and apply clustering.
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第14回
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Unsupervised Machine Learning
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Learn and apply principal component analysis.
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第15回
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Supervised Machine Learning
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Learn and apply neural networks.
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第16回
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Supervised Machine Learning
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Learn and apply convolutional neural networks.
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※AL（アクティブ・ラーニング）欄に関する注
・授業全体で、AL（アクティブ・ラーニング）が占める時間の割合を、それぞれの項目ごとに示しています。
・A〜Dのアルファベットは、以下の学修形態を指しています。
【A：グループワーク】、【B：ディスカッション・ディベート】、【C：フィールドワーク（実験・実習、演習を含む）】、【D：プレゼンテーション】
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