Core Algorithms and Data Structures

This unit expands foundational algorithmic concepts into core strategies and data structures used to solve increasingly complex problems. Students practice divide-and-conquer, combinatorics, advanced data structures (stacks, queues, heaps, search trees, graphs), graph algorithms (traversal, PageRank), big-data methods (streaming, MapReduce), and optimization and security heuristics to prepare for applied system design and project work in subsequent units.

Learning Objectives

• Analyze and compare the time and space complexity of algorithmic strategies and data structures (stacks, queues, heaps, search trees, and graph representations) to select appropriate solutions for given problems
• Apply divide-and-conquer, combinatorial, greedy, dynamic programming, and randomized techniques to design and implement correct algorithms for sorting, counting combinations, and optimization tasks
• Demonstrate graph modeling and solution methods by constructing graph representations, performing traversals and searches, sorting graph elements, and computing PageRank and routing heuristics on example networks
• Evaluate large-scale and applied approaches by designing streaming and MapReduce workflows, applying basic cryptographic primitives for confidentiality, and using local search and linear programming heuristics to solve practical optimization problems