{"id":1719,"date":"2023-03-27T09:53:10","date_gmt":"2023-03-27T06:53:10","guid":{"rendered":"https:\/\/www.ict.ihu.gr\/?post_type=course&#038;p=1719"},"modified":"2024-12-02T18:39:07","modified_gmt":"2024-12-02T16:39:07","slug":"%cf%80%ce%bb%ce%b508022","status":"publish","type":"course","link":"https:\/\/www.ict.ihu.gr\/en\/courses\/%cf%80%ce%bb%ce%b508022\/","title":{"rendered":"Data Mining"},"author":7,"template":"","meta":{"_acf_changed":false},"semester":[41],"course_type":[14],"acf":{"code":"\u03a0\u039b\u039508022","semester":41,"level":"1","teaching_activities":{"activity_1":{"description":"Lectures","weekly_hrs":2,"ects":5},"activity_2":{"description":"Practice Exercises","weekly_hrs":1,"ects":""},"activity_3":{"description":"Laboratory Exercises","weekly_hrs":1,"ects":""},"activity_4":{"description":"","weekly_hrs":"","ects":""},"activity_5":{"description":"","weekly_hrs":"","ects":""}},"type":14,"language":"Greek","erasmus":"\u039d\u03b1\u03b9","url":"https:\/\/elearning.cm.ihu.gr\/course\/view.php?id=216","prerequisites":"","instructors":[1434],"coordinator":[1434],"content":"<ul>\r\n \t<li>Introduction to data mining techniques. a) data types b) problems, c) applications, d) general data analysis and processing techniques.<\/li>\r\n \t<li>Data pre-processing: a) data cleaning, b) data transformation.<\/li>\r\n \t<li>Clustering: a) introduction to clustering methods, b) distance measures, c) k-means, d) hierarchical clustering.<\/li>\r\n \t<li>Data classification: (a) introduction to classification methods, (b) decision trees, (c) statistical techniques, (d) overfitting, (c) missing values, (d) model evaluation indexes, (e) classifiers Bayes classifiers, k-nearest neighbors f) classification in multidimensional time series data.<\/li>\r\n \t<li>Association rules: a) item sets b) support b) confidence c) a-priori algorithm.<\/li>\r\n \t<li>Dimensionality reduction techniques: Feature selection algorithms a) wrappers, b) filters, c) embedded.<\/li>\r\n \t<li>Knowledge discovery with Data Warehouses.<\/li>\r\n \t<li>Applications: Data mining techniques on biomedical data, business data, images data, text data and the Internet data.<\/li>\r\n \t<li>Google Analytics, Bussiness Analytics.<\/li>\r\n<\/ul>","goals":"Data mining is usually associated with the analysis of the large data sets present in the fields of big data, machine learning and artificial intelligence. The process looks for patterns, anomalies and associations in the data with the goal of extracting value. Here is the list of important areas where data mining is widely used: Healthcare, Market Basket Analysis, Manufacturing Engineering, CRM, Fraud Detection, Intrusion Detection, Customer Segmentation, Financial Banking.","skills":"<ul>\r\n \t<li>\u0391\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7, \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03cd\u03bd\u03b8\u03b5\u03c3\u03b7 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03b9\u03ce\u03bd, \u03bc\u03b5 \u03c4\u03b7 \u03c7\u03c1\u03ae\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03c9\u03bd \u03b1\u03c0\u03b1\u03c1\u03b1\u03af\u03c4\u03b7\u03c4\u03c9\u03bd \u03c4\u03b5\u03c7\u03bd\u03bf\u03bb\u03bf\u03b3\u03b9\u03ce\u03bd.<\/li>\r\n \t<li>\u039f\u03bc\u03b1\u03b4\u03b9\u03ba\u03ae \u0395\u03c1\u03b3\u03b1\u03c3\u03af\u03b1.<\/li>\r\n \t<li>\u03a3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03cc\u03c2 \u03ba\u03b1\u03b9 \u0394\u03b9\u03b1\u03c7\u03b5\u03af\u03c1\u03b9\u03c3\u03b7 \u0394\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u039c\u03b5\u03b3\u03ac\u03bb\u03bf\u03c5 \u038c\u03b3\u03ba\u03bf\u03c5.<\/li>\r\n \t<li>\u03a0\u03c1\u03bf\u03b1\u03b3\u03c9\u03b3\u03ae \u03c4\u03b7\u03c2 \u03b5\u03bb\u03b5\u03cd\u03b8\u03b5\u03c1\u03b7\u03c2, \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03ae\u03c2 \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae\u03c2 \u03c3\u03ba\u03ad\u03c8\u03b7\u03c2.<\/li>\r\n<\/ul>","teaching_methods":"<ul>\r\n \t<li>\u0398\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc \u03ad\u03b4\u03c1\u03b1\u03c2 \u03b4\u03b9\u03b4\u03b1\u03c3\u03ba\u03b1\u03bb\u03af\u03b1 \u03bc\u03b5 \u03c3\u03c5\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b5\u03bd\u03b5\u03c1\u03b3\u03ae \u03c3\u03c5\u03bc\u03bc\u03b5\u03c4\u03bf\u03c7\u03ae \u03c4\u03c9\u03bd \u03c6\u03bf\u03b9\u03c4\u03b7\u03c4\u03ce\u03bd. \u039a\u03b1\u03c4\u03ac \u03c4\u03b7 \u03b4\u03b9\u03ac\u03c1\u03ba\u03b5\u03b9\u03b1 \u03c4\u03bf\u03c5 \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03c3\u03b5\u03b9\u03c2 \u03c3\u03b5 power point.<\/li>\r\n \t<li>\u0395\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03ad\u03c2 \u0391\u03c3\u03ba\u03ae\u03c3\u03b5\u03b9\u03c2. \u0397\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03bd\u03b9\u03ba\u03cc \u03c5\u03bb\u03b9\u03ba\u03cc \u03b3\u03b9\u03b1 \u03c4\u03bf\u03c5\u03c2 \u03b1\u03bb\u03b3\u03bf\u03c1\u03af\u03b8\u03bc\u03bf\u03c5\u03c2 \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7\u03c2 \u0393\u03bd\u03ce\u03c3\u03b7\u03c2.<\/li>\r\n \t<li>\u0395\u03c0\u03af\u03bb\u03c5\u03c3\u03b7 \u0391\u03c3\u03ba\u03ae\u03c3\u03b5\u03c9\u03bd.<\/li>\r\n \t<li>\u0395\u03c0\u03af\u03b4\u03b5\u03b9\u03be\u03b7 \u03c3\u03c4\u03bf \u03c0\u03c1\u03bf\u03b2\u03bf\u03bb\u03b9\u03ba\u03cc \u03ba\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b7 \u03c0\u03af\u03bd\u03b1\u03ba\u03b1.<\/li>\r\n<\/ul>","ict_usage":"<ul>\r\n \t<li>\u03a7\u03c1\u03ae\u03c3\u03b7 \u03b5\u03be\u03b5\u03b9\u03b4\u03b9\u03ba\u03b5\u03c5\u03bc\u03ad\u03bd\u03bf\u03c5 \u03bb\u03bf\u03b3\u03b9\u03c3\u03bc\u03b9\u03ba\u03bf\u03cd. \u03a5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 \u039c\u03b1\u03b8\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae\u03c2 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1\u03c2 \u03bc\u03ad\u03c3\u03c9 \u03c4\u03b7\u03c2 \u03b7\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c0\u03bb\u03b1\u03c4\u03c6\u03cc\u03c1\u03bc\u03b1\u03c2.<\/li>\r\n \t<li>\u0397\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03bd\u03b9\u03ba\u03ad\u03c2 \u0391\u03c3\u03ba\u03ae\u03c3\u03b5\u03b9\u03c2 \u0391\u03c5\u03c4\u03bf\u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u03c2.<\/li>\r\n \t<li>\u0395\u03c0\u03b9\u03ba\u03bf\u03b9\u03bd\u03c9\u03bd\u03af\u03b1 \u03bc\u03b5 \u03c6\u03bf\u03b9\u03c4\u03b7\u03c4\u03ad\u03c2 \u03bc\u03ad\u03c3\u03c9 e-mail \u03ba\u03b1\u03b9 \u03c4\u03b7\u03c2 \u03b9\u03c3\u03c4\u03bf\u03c3\u03b5\u03bb\u03af\u03b4\u03b1\u03c2 \u03c4\u03bf\u03c5 \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2.<\/li>\r\n<\/ul>","teaching_organization":{"activity_1":{"description":"Lectures","workload":26},"activity_2":{"description":"Practice Exercises","workload":13},"activity_3":{"description":"Laboratory Exercises","workload":13},"activity_4":{"description":"Writing laboratory reports","workload":13},"activity_5":{"description":"Autonomous Study","workload":60},"activity_6":{"description":"","workload":""}},"students_evaluation":"\u039f \u03c4\u03b5\u03bb\u03b9\u03ba\u03cc\u03c2 \u03b2\u03b1\u03b8\u03bc\u03cc\u03c2 \u03c4\u03bf\u03c5 \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03b4\u03b9\u03b1\u03bc\u03bf\u03c1\u03c6\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ba\u03b1\u03c4\u03ac 60% \u03b1\u03c0\u03cc \u03c4\u03bf\u03bd \u03b2\u03b1\u03b8\u03bc\u03cc \u03c4\u03bf\u03c5 \u03b8\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03bf\u03cd \u03bc\u03ad\u03c1\u03bf\u03c5\u03c2 \u03ba\u03b1\u03b9 \u03ba\u03b1\u03c4\u03ac 40% \u03b1\u03c0\u03cc \u03c4\u03bf\u03bd \u03b2\u03b1\u03b8\u03bc\u03cc \u03c4\u03bf\u03c5 \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03bf\u03cd.\r\n<ol>\r\n \t<li>\u0397 \u03b3\u03c1\u03b1\u03c0\u03c4\u03ae \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03b8\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03bf\u03cd \u03bc\u03ad\u03c1\u03bf\u03c5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9:\r\n<ul>\r\n \t<li>\u0395\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03bb\u03bb\u03b1\u03c0\u03bb\u03ae\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae\u03c2.<\/li>\r\n \t<li>\u0395\u03c0\u03af\u03bb\u03c5\u03c3\u03b7 \u03c0\u03c1\u03bf\u03b2\u03bb\u03b7\u03bc\u03ac\u03c4\u03c9\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae\u03c2 \u03c4\u03c9\u03bd \u03b3\u03bd\u03ce\u03c3\u03b5\u03c9\u03bd \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03ba\u03c4\u03ae\u03b8\u03b7\u03ba\u03b1\u03bd.<\/li>\r\n \t<li>\u0395\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03b7\u03c2 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2.<\/li>\r\n \t<li>\u03a3\u03c5\u03b3\u03ba\u03c1\u03b9\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03af\u03c9\u03bd \u03b8\u03b5\u03c9\u03c1\u03af\u03b1\u03c2.<\/li>\r\n<\/ul>\r\n<\/li>\r\n \t<li>\u0397 \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b7 \u03c4\u03c9\u03bd \u03b1\u03c3\u03ba\u03ae\u03c3\u03b5\u03c9\u03bd \u03c4\u03bf\u03c5 \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03af\u03bf\u03c5 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9:\r\n<ul>\r\n \t<li>\u03a4\u03b7\u03bd \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c4\u03c9\u03bd \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03ce\u03bd \u03b4\u03b5\u03be\u03b9\u03bf\u03c4\u03ae\u03c4\u03c9\u03bd \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03ba\u03c4\u03ae\u03b8\u03b7\u03ba\u03b1\u03bd \u03bc\u03ad\u03c3\u03c9 \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b7\u03c2 \u03c4\u03c9\u03bd \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03ce\u03bd \u03b1\u03bd\u03b1\u03c6\u03bf\u03c1\u03ce\u03bd \u03ba\u03b1\u03c4\u03ac \u03c4\u03b7\u03bd \u03bf\u03c0\u03bf\u03af\u03b1 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03bf\u03cd \u03b5\u03be\u03bf\u03c0\u03bb\u03b9\u03c3\u03bc\u03bf\u03cd (30%).<\/li>\r\n \t<li>\u0393\u03c1\u03b1\u03c0\u03c4\u03ae \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b7\/\u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 (70%).<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ol>\r\n&nbsp;","bib_textbooks":"\u03a3\u03c5\u03b3\u03b3\u03c1\u03ac\u03bc\u03bc\u03b1\u03c4\u03b1 \u03bc\u03ad\u03c3\u03c9 \u03c4\u03bf\u03c5 \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u0395\u03a5\u0394\u039f\u039e\u039f\u03a3:\r\n<ol>\r\n \t<li>P.N. Tan, M. Steinbach, V. Kumar. \u0395\u03b9\u03c3\u03b1\u03b3\u03c9\u03b3\u03ae \u03c3\u03c4\u03b7\u03bd \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7 \u0394\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd, \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u03a4\u03b6\u03b9\u03cc\u03bb\u03b1, 2009. (Introduction to Data Mining, Addison Wesley, 2006 ) (\u0395\u03cd\u03b4\u03bf\u03be\u03bf\u03c2).<\/li>\r\n \t<li>M. H. Dunham. Data Mining: \u0395\u03b9\u03c3\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03a0\u03c1\u03bf\u03b7\u03b3\u03bc\u03ad\u03bd\u03b1 \u0398\u03ad\u03bc\u03b1\u03c4\u03b1 \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7\u03c2 \u0393\u03bd\u03ce\u03c3\u03b7\u03c2 \u03b1\u03c0\u03cc \u0394\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1,\u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u039d\u03ad\u03c9\u03bd \u03a4\u03b5\u03c7\u03bd\u03bf\u03bb\u03bf\u03b3\u03b9\u03ce\u03bd, 2004 (Data Mining: Introductory and Advanced Topics, Prentice Hall, 2003) (\u0395\u03cd\u03b4\u03bf\u03be\u03bf\u03c2).<\/li>\r\n<\/ol>\r\n\u03a3\u03c5\u03b3\u03b3\u03c1\u03ac\u03bc\u03bc\u03b1\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03b4\u03b9\u03b1\u03bd\u03ad\u03bc\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bc\u03ad\u03c3\u03c9 \u03c4\u03b7\u03c2 \u03b7\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c3\u03b5\u03bb\u03af\u03b4\u03b1\u03c2 \u03c4\u03bf\u03c5 \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2:\r\n<ol>\r\n \t<li>\u0391.\u03a4\u03a3\u0399\u039c\u03a0\u0399\u03a1\u0397\u03a3, \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7 \u0393\u03bd\u03ce\u03c3\u03b7\u03c2 - \u0395\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03ad\u03c2 \u03b1\u03c3\u03ba\u03ae\u03c3\u03b5\u03b9\u03c2, \u03a3\u03ad\u03c1\u03c1\u03b5\u03c2, 2018.<\/li>\r\n<\/ol>\r\n\u03a3\u03c5\u03bc\u03c0\u03bb\u03b7\u03c1\u03c9\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c0\u03c1\u03bf\u03c4\u03b5\u03b9\u03bd\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b3\u03c1\u03b1\u03c6\u03af\u03b1:\r\n<ol>\r\n \t<li>J. Han, M. Kamber, J. Pei. Data Mining : Concepts and Techniques (3rd edition), Morgan Kaufmann, 2011.<\/li>\r\n \t<li>M. Kantardzic. Data Mining: Concepts, Models, Methods, and Algorithms, Wiley-IEEE Press, 2002.<\/li>\r\n \t<li>I.H. Witten, E. Frank, M.A. Hall. Data Mining: Practical Machine Learning Tools and Techniques, (3rd edition), Morgan Kaufmann, 2011.<\/li>\r\n \t<li>\u039c. \u0392\u03b1\u03b6\u03c5\u03c1\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2 \u03ba\u03b1\u03b9 \u039c. \u03a7\u03b1\u03bb\u03ba\u03af\u03b4\u03b7. \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7 \u0393\u03bd\u03ce\u03c3\u03b7\u03c2 \u03b1\u03c0\u03cc \u0392\u03ac\u03c3\u03b5\u03b9\u03c2 \u0394\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd, \u03ba\u03b1\u03b9 \u03c4\u03bf\u03bd \u03a0\u03b1\u03b3\u03ba\u03cc\u03c3\u03bc\u03b9\u03bf \u0399\u03c3\u03c4\u03cc, - \u0393\u03b9\u03ce\u03c1\u03b3\u03bf\u03c2 \u0394\u03b1\u03c1\u03b4\u03b1\u03bd\u03cc\u03c2, 2005.<\/li>\r\n \t<li>\u0391. \u039d\u03b1\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2, \u0399. \u039c\u03b1\u03bd\u03c9\u03bb\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2, \u0395\u03b9\u03c3\u03b1\u03b3\u03c9\u03b3\u03ae \u03c3\u03c4\u03b7\u03bd \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03b9\u03c2 \u0391\u03c0\u03bf\u03b8\u03ae\u03ba\u03b5\u03c2 \u0394\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd, \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u039d\u03ad\u03c9\u03bd \u03a4\u03b5\u03c7\u03bd\u03bf\u03bb\u03bf\u03b3\u03b9\u03ce\u03bd, 2008.<\/li>\r\n<\/ol>","bib_journals":""},"_links":{"self":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1719"}],"collection":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course"}],"about":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/types\/course"}],"author":[{"embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/users\/7"}],"version-history":[{"count":26,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1719\/revisions"}],"predecessor-version":[{"id":9755,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1719\/revisions\/9755"}],"acf:post":[{"embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/staff\/1434"}],"acf:term":[{"embeddable":true,"taxonomy":"course_type","href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course_type\/14"},{"embeddable":true,"taxonomy":"semester","href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/semester\/41"}],"wp:attachment":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/media?parent=1719"}],"wp:term":[{"taxonomy":"semester","embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/semester?post=1719"},{"taxonomy":"course_type","embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course_type?post=1719"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}