Program Design with C (CS 201) - taught in Spring'06: website of the course & its most recent Syllabus
Programming Techniques (CS 324) - taught in Fall'05: website of the course & its most recent Syllabus
Database Systems (CS 435) - taught in Fall '04, Fall '05 and Fall '06
Database Theory (CS 535) - taught in Spring '05, and Fall '06
Data Mining (CS 530) - to be taught in Spring '07
Last revised: August, 2006 HOME PAGE
Brief Note on My Plagiarism Philosophy
Taking ideas (either by direct quotation or by paraphrase) from print, electronic or even hand-written sources without using end-of-sentence parenthetical documentation is called plagiarism. Plagiarism also occurs when students copy word-for-word a sentence or passage from a source without placing double quotation marks around those words. A good Internet site for learning how to document sources is A Guide for Writing Research Papers.
The course is designed to introduce the essential concepts of database systems: relational database model, fundamentals of data modeling and database design, Structured Query Language, and storage organization techniques applicable to DBMSs. At the end of the course, students should be able to: (1) Understand concepts of relational algebra, (2) Correctly design relational database model, (3) Implement and maintain relational database, (4) Efficiently use SQL.
The web page of this course can be found here and its most recent Syllabus is here.
Database Theory (CS 535) - graduate level course
The goal of this course is to present in detail a number of advanced concepts of database systems: spatial databases, multi-dimensional indexing techniques, advanced data modeling techniques, and a few emerging database models. The lectures should provide graduate students with sufficient foundation to conduct their own, but supervised research in the field of databases. Significant part of the course will be devoted to students’ individual research, conducted during work on graduate projects. The students are encouraged to extend the material presented during the course by individual studies and by the development of projects intersecting their own research interests and the gathered database expertise.
At the end of the course, students should be able to: (1) Understand concepts of spatial databases, (2) Understand methodology of data warehousing, (3) Be familiar with Graph-formatted Data Storage and Retrieval, (4) Develop projects involving processing of large repository of complex data, and (4) Present their findings on the conducted research in the form of scientific publication.
The web page of this course can be found here and its most recent Syllabus is here.
Data Mining (CS 530) - graduate level course
The goal of this course is to present in detail a chosen number of topics from Data Mining area: Data Preparation, Association Rules, Classification, Prediction, Cluster Analysis, and finally Mining Complex Types of Data. The lectures should provide graduate students with sufficient foundation to conduct their own, but supervised research in the field of data analysis. Students will gain hands on experience on the chosen aspect of Data Mining field through completion of their own graduate research project, which will be reviewed by their peers at the end of the semester.
At the end of the course, students should be able to: (1) Understand advanced aspects of popular data mining techniques, (3) Develop projects involving computational analysis of large repository of multidimensional data, (4) Present their findings on the conducted research in the form of scientific publication.
The web page of this course can be found here.