Core Algorithms and Data Structures

This unit expands foundational computing skills into a broad set of algorithmic design patterns and data structures used to solve real-world problems. Students explore divide-and-conquer, greedy and dynamic programming, randomized and heuristic methods, graph algorithms, streaming and distributed paradigms (MapReduce), and practical tools (notebooks, PageRank, basic cryptography) to prepare for applied projects in subsequent units.

Learning Objectives

• Analyze the performance and trade-offs of fundamental data structures (stacks, queues, search trees, heaps) and representations of graphs, using complexity metrics to justify selection for specific problems
• Apply algorithm design patterns—divide-and-conquer, greedy strategies, dynamic programming, and randomized approaches—to formulate correct solutions and estimate their time and space complexity
• Demonstrate the design and implementation of algorithms for large-scale or streaming data (including MapReduce patterns and PageRank) and use notebooks to document, test, and present results
• Evaluate optimization and search techniques (local search, heuristics, linear programming, routing heuristics) and basic cryptographic primitives to compare solution quality, scalability, and applicability to given tasks