Harrisburg University TA Courses

Data Structures and Algorithms (CISC 610)

This course emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis and implementation. This class overs techniques used to analyze problems and algorithms (including asymptotic, upper/lower bounds, best/average/worst case analysis, amortized analysis, complexity), basic techniques used to design algorithms (including divide and conquer/greedy/dynamic programming/heuristics, choosing appropriate data structures) and important classical algorithms (including sorting, string, matrix, and graph algorithms) and data structures.

Discrete Mathematics I (MATH 210)

This course provides the student with an understanding of multiple mathematical concepts and methods, which shape the foundation of modern information science in a form that is relevant and useful. Discrete mathematics plays a fundamental role for computer science, which is similar to that played by calculus for physics and engineering.

Analytics II: Principles and Applications (ANLY 510)

This course takes an applied perspective and provides the statistical tools and analytic thinking techniques needed to: formulate a clear hypothesis, determine the most efficient method to obtain required data, determine and apply the proper statistical techniques to the resulting data, and effectively convey the results to both experts and laypersons.

Data Engineering and Mining (CISC 520)

This course addresses the emerging issues in designing, building, managing, and evaluating advanced data-intensive systems and applications. Data engineering is concerned with the role of data in the design, development, management, and utilization of complex computing/information systems.

Discrete Mathematics II (MATH 310)

This course ensures that the computer science student reaches the level of mathematical maturity necessary for the study of Computer and Information Science. Topics covered draw on current material from the study of graphs, trees, relations, algorithms and models of computation.

Operating Systems Design (CSE 511)

Concurrent programming; design of I/O subsystem, memory management, and user interface; kernel design; deadlocks, protection and security; case studies.

Programming and Computation I: Fundamentals (CMPSC 131)

This course introduces the fundamental concepts and processes of solving computational problems through the design, implementation, testing and evaluation of efficient and robust computer programs. The concepts include basic computational constructs found in imperative, object-oriented and functional programming languages such as iteration, conditionals, functions, recursion, and datatypes.

Programming Techniques (CISC 260)

This course is a systematic study of programming languages and algorithms organized around the unifying concept of data and code abstraction. Emphasis is placed on ADT-based and object-oriented design, incremental development and testing, and comparison of data structure implementations.