Course Descriptions

Algorithm analysis, linked lists, stacks, queues, trees, hashing, priority queues, sorting, graph data structures and graph algorithms.

Entity-relationship model, database conceptual design, relational algebra, SQL, storage and indexing, B+ trees, hash indexes, query evaluation, external sorting, query optimization, normalization.

Principles of human computer interaction. Elements of interactive computer systems, windows, and input devices. Window systems and dialogue control. Design of dialogues for interactive systems. Psychological, physiological, linguistic, and perceptual factors. Advantages and disadvantages of various interaction techniques, command language syntaxes, and data presentations. Design methodology and guidelines.

Divide-and-conquer strategy, graph algorithms, depth first search, breadth first search, shortest path algorithms, greedy strategy, dynamic programming, linear programming, numeric algorithms, NP-complete problems, approximation algorithms.

Process abstraction, program loading and execution, multithreading, scheduling, synchronization, memory management, file systems, mass storage, I/O systems.

Network architecture, network protocols, application layer, transport, congestion, routing, link protocols, multiple access, overview of communication architectures.

Assembly language, computer arithmetic, datapath and control, pipelining, memory hierarchy, cache.

Design and development of a project for a computer engineering problem under the supervision of an academic advisor; submission of the results in the form of a project report and oral presentation.

Basic topics in parametric statistics; estimation, confidence intervals, and hypothesis testing; analysis of variance, regression and correlation analysis; goodness of fit tests. Elementary design of experiments and data collection; computer implementations using available up-to-date statistical software.