Data Structures and Algorithms Prerequisite (Non-credit version)
Course Syllabus
Data Structures and Algorithms
Course Description
The focus of this course is how data structures and algorithms impact the computational
complexity (time and space) of programs. It is assumed that you have some familiarity with the
data structures of stacks, queues, linked lists, and binary search trees (BSTs). This course
additionally covers the data structures of heaps, hash tables, balanced variants of BSTs (for
example, red-black, 2-3, or splay trees), and graphs (undirected and directed, weighted and
unweighted). Algorithmic techniques covered include divide-and-conquer, dynamic
programming, and greedy. While most algorithms are analyzed in the worst or average case,
also of interest are lower bounds, and amortized and probabilistic analyses.
Specific topics covered include:
● Introduction to Essential Data Structures
● Implementation of Data Structures
● Introduction to Algorithms and Algorithm Strategies
● Introduction to Run Time Analysis and Big-O
● Analysis of Algorithms
● Implementation of Algorithms
Learning Outcomes
Learners completing this course will be able to:
● Define data structures such as heaps, balanced trees, and hash tables.
● Explain how to use a specific data structure in modeling a given problem.
● Identify, construct, and clearly define a data structure that is useful for modeling a given
problem.
● State some fundamental algorithms such as merge sort, topological sort, Prim’s and
Kruskal’s algorithm, and algorithmic techniques such as dynamic programming and
greedy algorithms.
● Use a specific algorithmic technique in solving a given problem.
● Design an algorithm to solve a given problem.
● Define the notions of worst-, best-, and average-case running times of algorithms.
● Analyze and compare different asymptotic running times of algorithms.
● Analyze a given algorithm and determine its asymptotic running time.
● Combine fundamental data structures and algorithmic techniques in building a complete
algorithmic solution to a given problem.
