{"id":143,"date":"2022-02-07T16:39:53","date_gmt":"2022-02-07T07:39:53","guid":{"rendered":"http:\/\/bmil.jnu.ac.kr\/?page_id=143"},"modified":"2022-03-16T16:05:28","modified_gmt":"2022-03-16T07:05:28","slug":"lecture","status":"publish","type":"page","link":"https:\/\/bmil.jnu.ac.kr\/?page_id=143","title":{"rendered":"LECTURE"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; background_image=&#8221;http:\/\/bmil.jnu.ac.kr\/wp-content\/uploads\/2022\/02\/subheader-bg1.jpg&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.14.7&#8243; _dynamic_attributes=&#8221;content&#8221; _module_preset=&#8221;default&#8221; text_font=&#8221;Lato|700||||on|||&#8221; text_text_color=&#8221;#000000&#8243; text_font_size=&#8221;30px&#8221; text_letter_spacing=&#8221;1px&#8221; text_orientation=&#8221;center&#8221; global_colors_info=&#8221;{}&#8221;]@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF90aXRsZSIsInNldHRpbmdzIjp7ImJlZm9yZSI6IiIsImFmdGVyIjoiIn19@[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||40px||false|false&#8221; custom_padding=&#8221;5px||5px||true|false&#8221; hover_enabled=&#8221;0&#8243; border_width_bottom=&#8221;2px&#8221; border_color_bottom=&#8221;#1F5CAA&#8221; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h3>Artificial Intelligence<\/h3>\n<p>The main purpose of this course is to provide the most fundamental knowledge about AI to the students so that they can understand what the AI is. The course contains the following topics: search, planning, decision-making, and machine learning. Also, we will try to make an intelligent system. Each student should survey an interesting topic and try to make it smarter using AI techniques.<\/p>\n<p>[\/et_pb_text][et_pb_text _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||40px||false|false&#8221; custom_padding=&#8221;5px||5px||true|false&#8221; hover_enabled=&#8221;0&#8243; border_width_bottom=&#8221;2px&#8221; border_color_bottom=&#8221;#1F5CAA&#8221; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h3>Machine Learning<\/h3>\n<p>This course provides a broad introduction and fundamental knowledge about machine learning. Topics are mainly categorized into the following two parts: supervised and unsupervised learning. To understand supervised learning, we will learn linear regression, logistic regression, decision tree, SVM, and neural networks. For unsupervised learning, we will learn clustering, association rule mining, dimensionality reduction, kernel methods. The course will also perform practical machine learning projects.<\/p>\n<p>[\/et_pb_text][et_pb_text _builder_version=&#8221;4.14.7&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||40px||false|false&#8221; custom_padding=&#8221;5px||5px||true|false&#8221; hover_enabled=&#8221;0&#8243; border_width_bottom=&#8221;2px&#8221; border_color_bottom=&#8221;#1F5CAA&#8221; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h3>Big Data System<\/h3>\n<p>This course provides fundamental knowledge on Big Data handling. For this, we will learn Hadoop Ecosystem tools such as HDFS, MapReduce, Hive, Spark, and Sqoop. 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The course contains the following topics: search, planning, decision-making, and machine learning. Also, we will try to make an intelligent system. 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