The MBC information booklet - RMIT University

Chapter 3: Advanced Databases
3.2 Courses
3.2.1 COSC2306—
Algorithms for
Efficient Data
Engineering
3.2.2 COSC2111—
Data
Warehousing
and Data Mining
18
Note: This is a Masters-level course.
Aim
This course presents state of the art algorithms for data manipulation and advanced
applications. Content includes advanced compression techniques, perfect minimal
hashing, randomised algorithms and cache-aware programming.
Objectives
On completion of this courses students should be able to:
• Improve the efficiency of their code by applying suitable heuristics
• Choose appropriate algorithms and data structures to solve a complex problem
• Compare and evaluate strengths and weaknesses of data structures, and
communicate this understanding
Prerequisites
• COSC1285 Advanced Programming Techniques
Syllabus
1. The programmer’s toolkit:
• Hash tables
• Heaps
• Splay trees
• Tries
2. Beyond procedural structured programming:
• Lookup tables to accelerate elementary functions.
• Goto for clean break out of nested loops
• Avoiding pointer de-referencing.
• Cache aware algorithms, with a focus on sorting (Burst sort).
3. String search and pattern matching:
• Suffix trees and tries.
• Repository data structures, such as splay trees, ternary search trees, burst
tries.
4. Perfect minimal hashing.
5. Randomized algorithms.
6. Advanced Compression Techniques, including: arithmetic coding, Burrows-
Wheeler Transform
Note: This is a Masters-level course.
Course Description
This course is about the deployment of advanced database techniques in large
enterprises. It aims to provide you with up-to-date conceptual and practical knowledge
on recent developments in database technology, specifically data mining and data
warehousing. At the end of this course, students will understand concepts, principles and
techniques of data warehousing and data mining.
Lecture topics include: Overview of data warehousing, Data warehouse design, OLAP
technologies, Data cubing, Overview of knowledge discovery and data mining, Data
mining techniques, Classification, Clustering, and Knowledge discovery in data
warehouses.
Pre-requisite Courses and Assumed Knowledge and Capabilities
• Fundamental knowledge in relational database concepts, including relational
modelling & design, relational algebra & SQL, conceptual modelling, and
transactions & concurrency, equivalent to ISYS1055 Introduction to Database
Systems