Algorithm Design and Data Structures

This unit expands foundational programming skills into algorithm design, advanced data structures, and applied problem-solving techniques used in real-world systems. Students will study divide-and-conquer, trees and heaps, graph algorithms (including PageRank and traversal), streaming and MapReduce, cryptography basics, and a range of optimization paradigms to prepare for higher-level algorithmic applications.

Learning Objectives

• Analyze and compare time and space complexity and trade-offs of core data structures and algorithms, including divide-and-conquer strategies, stacks, queues, search trees, heaps, and sorting methods
• Apply algorithmic techniques to design and implement solutions for graph-based problems, data streaming, and parallel processing frameworks (e.g., PageRank, traversal, MapReduce), demonstrating correct representations and traversals
• Demonstrate the formulation and implementation of optimization approaches using greedy algorithms, dynamic programming, randomized methods, local search, and linear programming heuristics, and measure their correctness and performance
• Evaluate practical system constraints such as scalability, streaming limits, cryptographic considerations, and heuristic routing for robotics, selecting appropriate algorithms and data structures based on problem requirements