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Subject Syllabus

AL-402 - Analysis & Design of Algorithms

AIML • SEMESTER-4

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

Definitions of algorithms and complexityTime and Space ComplexityTime space tradeoffVarious bounds on complexityAsymptotic notationRecurrences and Recurrences solving techniquesIntroduction to divide and conquer techniqueExample: binary search, merge sort, quick sort, heap sort, strassen’s matrix multiplication etc.Code tuning techniques: Loop Optimization, Data Transfer Optimization, Logic Optimization, etc.
Study of Greedy strategyExamples of greedy method like optimal merge patterns, Huffman coding, minimum spanning trees, knapsack problem, job sequencing with deadlines, single source shortest path algorithm etc.Correctness proof of Greedy algorithms
Concept of dynamic programmingProblems based on this approach such as 0/1 knapsack, multistage graph, reliability design, Floyd-Warshall algorithm etc.
Backtracking concept and its examples like 8 queen’s problem, Hamiltonian cycle, Graph colouring problem etc.Introduction to branch & bound methodExamples of branch and bound method like travelling salesman problem etc.Meaning of lower bound theory and its use in solving algebraic problemIntroduction to parallel algorithms
Advanced tree and graph algorithmsNP-hard and NP-complete problemsApproximations AlgorithmsData Stream AlgorithmsIntroduction to design and complexity of Parallel Algorithms