Computer Science Fundamentals: Algorithms & Data Structures
Master asymptotic complexity, formal proofs, cache-conscious data structures, and production-grade algorithms.
This intermediate course bridges rigorous algorithmic theory with production software performance engineering. Students learn to analyze recurrence relations, construct balanced trees, and prove computational complexity bounds while also profiling cache efficiency and implementing lock-free data structures. The curriculum provides dual pathways for academic mastery and high-performance industry execution.
Curriculum
Two complete tracks. Study either or both — each has its own exam and certificate.
A mathematically rigorous exploration of formal algorithmic analysis, recurrence derivations, abstract data type invariants, and structural intractability.
Mathematical foundations of computational complexity, recursion relations, and lower bounds for comparison sorting.
- Asymptotic Growth Orders and Limit Theorems Lab35 min
- Divide-and-Conquer Recurrence Solutions Lab40 min
- Information-Theoretic Sorting Lower Bounds Lab30 min
Careers this prepares you for
- Software Systems Engineer
- Backend Infrastructure Engineer
- Algorithm Engineer
- High-Frequency Trading Developer