CSC-FPX4020 covers the algorithms and data structures foundational to computer science, along with the efficiency analysis that determines whether a solution scales.
Fundamental data structures
CSC-FPX4020 covers core data structures — arrays, linked lists, trees, hash tables, graphs — and how the choice of structure shapes what operations are efficient.
Algorithms and efficiency analysis
The course covers foundational algorithms and Big O analysis, the framework for reasoning about how an algorithm's performance scales with input size.
Key topics in CSC-FPX4020
- Core data structures
- Algorithm design techniques
- Big O complexity analysis
- Sorting and searching algorithms
- Choosing the right data structure
- Efficiency trade-offs
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Worked example: data structure choice changes everything
- Searching a list: Finding an item in an unsorted array requires checking each element — slow as the data grows
- Searching a hash table: The same lookup is nearly instant regardless of size
- Lesson: Choosing the right data structure can transform an operation from unacceptably slow to nearly instant, which is exactly why data structure knowledge is foundational
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Frequently asked questions
Big O notation describes how an algorithm's resource requirements (usually time) grow as the input size grows, and this matters enormously because an algorithm that works fine on small test data can become unusably slow on real-world-scale data if it scales poorly — the difference between an algorithm that scales linearly and one that scales quadratically can be the difference between a response in milliseconds and one that takes hours on large inputs. CSC-FPX4020 teaches Big O analysis because it's the framework for reasoning about whether a solution will actually scale, allowing programmers to predict and compare performance characteristics before deploying code, rather than discovering only in production that an approach that seemed fine cannot handle real data volumes.
Different data structures make different operations efficient or inefficient — a hash table offers nearly instant lookups but no inherent ordering, an array offers fast indexed access but slow insertion in the middle, a tree offers efficient ordered operations — so the same task can be fast or painfully slow depending purely on which structure holds the data. CSC-FPX4020 emphasizes data structure choice because selecting the right structure for the operations a program actually performs most is one of the highest-leverage decisions in software efficiency: matching the structure to the access patterns can transform an operation from unacceptably slow to nearly instant, while a poor choice can bottleneck an otherwise well-written program.