{"ModuleCode":"CS4225","ModuleTitle":"Massive Data Processing Techniques in Data Science","Department":"Computer Science","ModuleDescription":"Data science incorporates varying elements and builds on techniques and theories from many fields, including statistics, data engineering, data mining, visualization, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. Data science seeks to use all available and relevant data to effectively tell a story that can be easily understood by non-practitioners. In this module, students will learn various massive data processing techniques that are used in data science with emphasis on the algorithmic and mathematical properties of these techniques.","ModuleCredit":"4","Workload":"2-1-0-3-4","Prerequisite":"CS3223 Database Systems Implementation","ExamDate":"2015-04-28T09:00+0800","ExamDuration":"P2H","ExamVenue":"SOC SR11","Types":["Module"],"Lecturers":["Tung Kum Hoe Anthony"],"IVLE":[{"Announcements":null,"Forums":[],"Workbins":[],"Webcasts":[],"Gradebooks":[],"Polls":[],"Multimedia":[],"LessonPlan":[],"ID":"4ce8c55e-8aab-4472-b1b0-49a1e0f18b28","CourseLevel":"1","CourseCode":"CS4225","CourseName":"MASSIVE DATA PROCESSING TECHNIQUES IN DATA SCIENCE","CourseDepartment":"","CourseSemester":"Semester 2","CourseAcadYear":"2014/2015","CourseOpenDate":"/Date(1420387200000+0800)/","CourseOpenDate_js":"2015-01-05T00:00:00","CourseCloseDate":"/Date(1433606340000+0800)/","CourseCloseDate_js":"2015-06-06T23:59:00","CourseMC":"0","isActive":"N","Permission":"S","Creator":{"UserID":null,"Name":"Tung Kum Hoe Anthony","Email":null,"Title":null,"UserGuid":"22187e5f-db68-4fa4-9918-8af93b169dbe","AccountType":null},"hasGradebookItems":false,"hasTimetableItems":true,"hasGroupsItems":false,"hasClassGroupsForSignUp":false,"hasGuestRosterItems":true,"hasClassRosterItems":true,"hasWeblinkItems":false,"hasLecturerItems":true,"hasDescriptionItems":true,"hasReadingItems":true,"hasAnnouncementItems":false,"hasProjectGroupItems":false,"hasProjectGroupsForSignUp":false,"hasConsultationItems":false,"hasConsultationSlotsForSignUp":false,"hasLessonPlanItems":false,"Badge":0,"BadgeAnnouncement":0,"WebLinks":[],"Lecturers":[{"ID":"dc0fcae0-d521-4452-9a58-3530d61d912e","User":{"UserID":null,"Name":"Tung Kum Hoe Anthony","Email":null,"Title":null,"UserGuid":"22187e5f-db68-4fa4-9918-8af93b169dbe","AccountType":null},"Role":"Lecturer ","Order":1,"ConsultHrs":null},{"ID":"876d2e60-c0da-42bb-afec-4d0ca4fd03ea","User":{"UserID":null,"Name":"ZHENG KAIPING","Email":null,"Title":null,"UserGuid":"390facde-3085-434e-89ad-e7e84186b929","AccountType":null},"Role":"Teaching Assistant ","Order":2,"ConsultHrs":null}],"Descriptions":[{"ID":"1e5f053b-8835-4692-be49-41f07234cfff","Title":"Learning Outcomes","Description":"Data science incorporates varying elements and builds on techniques and theories from many fields, including statistics, data engineering, data mining, visualization, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. Data science seeks to use all available and relevant data to effectively tell a story that can be easily understood by non-practitioners. In this module, students will learn various massive data processing techniques that are used in data science with emphasis on the algorithmic and mathematical properties of these techniques.","Order":1},{"ID":"2e5f053b-8835-4692-be49-41f07234cfff","Title":"Prerequisites","Description":"CS3223 Database Systems Implementation","Order":2},{"ID":"3ebc6d65-cf11-4d5c-807a-0e98117cfecf","Title":"Workload","Description":"2-1-0-3-4
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