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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.

Asymptotic notationCode tuning techniques: Loop Optimization, Data Transfer Optimization, Logic Optimization, etc.Definitions of algorithms and complexityExample: binary search, merge sort, quick sort, heap sort, strassen’s matrix multiplication etc.Introduction to divide and conquer techniqueRecurrences and Recurrences solving techniquesTime and Space ComplexityTime space tradeoffVarious bounds on complexity
Correctness proof of Greedy algorithmsExamples of greedy method like optimal merge patterns, Huffman coding, minimum spanning trees, knapsack problem, job sequencing with deadlines, single source shortest path algorithm etc.Study of Greedy strategy
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.Examples of branch and bound method like travelling salesman problem etc.Introduction to branch & bound methodIntroduction to parallel algorithmsMeaning of lower bound theory and its use in solving algebraic problem
Advanced tree and graph algorithmsApproximations AlgorithmsData Stream AlgorithmsIntroduction to design and complexity of Parallel AlgorithmsNP-hard and NP-complete problems