1 false COMP3420 <p>This course examines the design of databases and data warehouses and their use for data mining; and investigates associated issues. Topics may include: relational theory and conceptual modelling; privacy and security; statistical databases; distributed databases; data warehousing; data cleaning and integration; and data mining concepts and techniques.</p> C 1 false 10787 <p>Two assignments (40 marks); Final Exam (60 marks)</p> 1 1 <p>On completion of this course, the students should have gained a good understanding of basic concepts, principles and techniques in data warehousing and data mining. Specifically,the students are able to perform the following tasks. </p> <ul><li>perform data modeling</li><li>apply OLAP techniques for mulit-dimensional data analysis</li><li>apply datacubing techniques </li><li>develop general skill of data warehousing project management</li><li>obtain the general knowledge on the design and implementation of data warehouses </li><li>be able to apply data mining techniques for knowledge discovery</li><li>&nbsp;develop in-depth understanding of fundamental data mining algorithms </li><li>perform data mining in data warehouses.</li></ul> 0 Advanced Databases and Data Mining 6 6 <p>The following text book will be used for this course:</p> <ul><li>Han, Jiawei &amp; Kamber, Micheline <em> Data Mining: Concepts and Techniques </em>Morgan Kaufmann Publishers, 2nd Edition, March 2006.</li></ul> <p>The following reference book is recommended for this course:</p> <ul><li>Elmasri and Navathe <em>Fundamentals of Database Systems</em>Addison-Wesley, 5th Edition, 2007.</li></ul> 6 <p>COMP1100 or COMP2720; COMP2400; 6 units of 2000-level IT courses; and 6 units of 1000-level MATH/STAT courses.</p> Advncd Databases and Data Mng Band 2 Computer Science <p>Thirty one-hour lectures and six two-hour tutorials</p> 2010