[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-317485-105":59,"doc-detail-317485-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","comp7990-principles-and-practices-of-data-analytics","COMP7990 Principles and Practices of Data Analytics","","Course COMP7990 introduces core principles of data management and analysis, covering relational database representation, SQL query formulation, and the end-to-end workflow of collecting, storing, analyzing, and visualizing data. The curriculum expands into data analytics, data mining, and statistical analysis, with an emphasis on visualization concepts and communicating results effectively. It also addresses data security and privacy management, including legal foundations and privacy protection principles. 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It also includes relational database representation and SQL query formulation.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What learning outcomes are expected after completing the course?",{"text":118,"@type":114},"Students should be able to describe database management fundamentals, explain data analysis and mining concepts, and understand visualization. They should also formulate SQL queries and perform statistical analysis and visualization to present results.",{"name":120,"@type":111,"acceptedAnswer":121},"How is student performance assessed?",{"text":122,"@type":114},"Assessment uses continuous assessment (40%) and a final examination (60%). 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It  \ncovers various topics including database management, data analytics, data mining, data visualization, and data privacy. It is expected that students can grasp numeracy and practical skills about how to collect, store, analyze, and visualize data.  \nPrerequisite: Nil  \nCourse Intended Learning Outcomes (CILOs):  \nUpon successful completion of this course, students should be able to:  \n\n| No. | Course Intended Learning Outcomes (CILOs) |\n| --- | --- |\n|  | Knowledge |\n| 1 | Describe fundamentals of database management |\n| 2 | Explain concepts of data analysis techniques and data mining algorithms |\n| 3 | Describe and explain concepts of data visualization |\n| 4 | Describe concepts and legal foundations of data security and privacy |\n|  | Professional Skill |\n| 5 | Formulate SQL queries on the database |\n| 6 | Conduct statistical analysis and design visualization to present analysis results |\n\nCalendar Description: This course introduces principal concepts of data management and analysis.  \nTopics mainly include: 1) representation of data in relational database and formulation of data query; 2) knowledge of data analytics and data mining; 3) data visualization concepts; 4) principles of data security and privacy management.  \nTeaching and Learning Activities (TLAs):  \n\n| CILOs | Type ofTLA |\n| --- | --- |\n| 1-4 | Students will learn the fundamentals of data management, analysis, and visualization concepts via lectures and tutorials. |\n| 5-6 | Students will gain practical experiences via laboratory sessions and assignments. |\n\nAssessment:  \n\n| No. | Assessment Methods | Weighting | CILOs to be\u003Cbr>addressed | Description of Assessment Tasks |\n| --- | --- | --- | --- | --- |\n| 1 | Continuous\u003Cbr>Assessment | 40% | 1-6 | Continuous assignments are designed to measure how well students have learnt the fundamentals of data management, analysis, and visualization techniques. Assignments and lab exercises are designed to evaluate students’ knowledge and skills. Quizzes are used to determine to what extent the students have achieved the expected learning outcome. |\n| 2 | Examination | 60% | 1-4 | Final examination questions are designed to identify how far students have achieved intended learning outcomes. Questions will primarily assess students’knowledge in managing, analyzing and visualizing data. |\n\nAssessment Rubrics:  \n\n| Excellent (A) | 􀁸 Achieve the eight CILOs, demonstrating a mastery of fundamentals of data management, analysis and visualization |\n| --- | --- |\n\n\n|  | 􀁸\u003Cbr>􀁸 | Have a thorough understanding of concepts and technologies involved, and be able to explain and highlight the key points of these concepts and technologies\u003Cbr>Able to perform data storage, analysis and visualization |\n| --- | --- | --- |\n| Good (B) | 􀁸\u003Cbr>􀁸\u003Cbr>􀁸 | Achieve the eight CILOs, demonstrating a good understanding of fundamentals of data management, analysis and visualization\u003Cbr>Have a good understanding of concepts and technologies involved, and be able to explain and highlight the key points of these concepts and technologies\u003Cbr>Able to perform data storage, analysis and visualization for familiar cases |\n| Satisfactory (C) | 􀁸\u003Cbr>􀁸\u003Cbr>􀁸 | Achieve most of CILOs, demonstrating a basic level of understanding of fundamentals of data management, analysis and visualization\u003Cbr>Have a basic understanding of concepts and technologies involved\u003Cbr>Able to perform data storage, analysis and visualization for simple cases |\n| Fail (F) | 􀁸\u003Cbr>􀁸\u003Cbr>􀁸 | Achieve less than three of CILOs, having little understanding of fundamentals of data management, analysis and visualization\u003Cbr>Have little understanding of concepts and technologies involved, and unable to explain and highlight the key points of these concepts and technologies\u003Cbr>Unable to perform data storage, analysis and visualization for si","cbCain9VuPYdt8nQ","https://ap.wps.com/l/cbCain9VuPYdt8nQ","pdf",254858,"English","# Course Aims\n# Course Intended Learning Outcomes (CILOs)\n## Knowledge\n## Professional Skill\n# Calendar Description\n# Teaching and Learning Activities (TLAs)\n# Assessment\n## Continuous Assessment\n## Examination\n# Assessment Rubrics\n# Course Content and CILOs Mapping\n# References\n# Course Content","[{\"question\":\"What are the main topics covered in COMP7990?\",\"answer\":\"The course focuses on data management, data analytics, data mining, data visualization, and data security and privacy. It also includes relational database representation and SQL query formulation.\"},{\"question\":\"What learning outcomes are expected after completing the course?\",\"answer\":\"Students should be able to describe database management fundamentals, explain data analysis and mining concepts, and understand visualization. They should also formulate SQL queries and perform statistical analysis and visualization to present results.\"},{\"question\":\"How is student performance assessed?\",\"answer\":\"Assessment uses continuous assessment (40%) and a final examination (60%). Continuous tasks evaluate knowledge and skills through assignments, lab exercises, and quizzes, while the exam tests how far students have achieved the intended learning outcomes.\"}]","COMP7990 Principles and Practices of Data Analytics | PDF",1789933623]