CS 300 - Data Structures for Everyone

Units: 3 ; Breadth Area: GE-UDB
Further development of programming and problem solving skills with emphasis on data structures. Topics include stacks, queues, doubly-linked/circularly-linked lists, trees, heaps, priority queues and graphs. Algorithmic analysis and asymptotic notation; binary search, heapsort, merge sort, quicksort, and radix sort.

Strongly Recommended Preparation: Upper division status (greater than 60 earned semester units) and completion of lower division Areas B1-B3.
Prerequisites: Completion of GE Areas A1, A2, A3 and B4 with grade C- (CR) or better; and CS 100, CS 200.
Credit Restrictions: Not for Computer Science major or minor credit.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F or CR/NC (student choice).
Breadth Area(s) Satisfied: GE-UDB- Upper Division Science Inquiry and Quantitative Reasoning
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Author computer programs to solve a variety of computational problems;
Apply object-oriented techniques to the implementation of abstract data types and supporting methods;
Utilize data structures to store, retrieve, and edit data;
Evaluate the characteristics of a problem in order to determine the most efficient search or sorting procedure to select;
Analyze the time and space efficiency of commonly-used algorithms.

UD-B. Upper-division Science Inquiry and Quantitative Reasoning Learning Outcomes

demonstrate advanced and/or focused science or quantitative content knowledge in a specific scientific field, using appropriate vocabulary and referencing appropriate concepts (such as models, uncertainties, hypotheses, theories, and technologies);
apply advanced quantitative skills (such as statistics, algebraic solutions, interpretation of graphical data) to scientific problems and evaluate scientific claims;
demonstrate understanding of the nature of science and scientific inquiry and the experimental and empirical methodologies used in science to investigate a scientific question or issue; and
apply science content knowledge to contemporary scientific issues (e.g., global warming) and technologies (e.g., cloning), where appropriate.