Analysis and Design of Algorithms
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Follow on Instagram for UpdatesAnalysis and Design of Algorithms Syllabus — Unit-wise Content
The official GTU curriculum for Analysis and Design of Algorithms (subject code BE05000141) as prescribed for AI & DS · Semester 5 divides the course into 8 units, covering 61 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (BE05000141)Unit 1 Introduction and Analysis of Algorithm
- Introduction to algorithm
- Properties of good algorithm
- Best and worst case analysis
- Asymptotic Notations (Big Oh, Big Theta
- Big Omega)
- Disjoint set operations
- Union and find algorithms
Unit 2 Analysis of Sorting Algorithms
- Comparison based sorting: Bubble sort
- Selection sort
- Insertion sort
- Heap sort
- Sorting in linear time : Bucket sort
- Radix sort and Counting sort
Unit 3 Divide and Conquer
- General method
- Recurrence and different methods to solve recurrence
- Problem solving using Divide and Conquer: Binomial Coefficient
- Binary Search
- Max-Min problem
- Merge Sort
- Quick Sort
- Strassen’s algorithm for Matrix Multiplication
Unit 4 Dynamic Programming
- General method
- Elements of Dynamic Programming
- The Principle of Optimality Problem Solving using Dynamic Programming: Making Change Problem
- Knapsack problem
- Multi stage graph
- Matrix chain multiplication
- Longest Common Subsequence
- Shortest Common Supersequence
Unit 5 Greedy Algorithm
- General method
- Characteristics of greedy algorithms
- Elements of greedy strategy Problem solving using Greedy method: Making change problem
- Activity selection problem
- Knapsack problem (0/1 and Fractional)
- Job Scheduling Problem
- Huffman Trees
Unit 6 Graph Algorithms
- Types of graph
- Representation Graph
- Traversing Graphs: Depth First Search, and Breath First Search
- Topological sort
- Strongly Connected components
- Problems solving: Finding articulation point
- Minimum Spanning trees (Kruskal’s algorithm
- Prim’s algorithm) using greedy approach
- Dijkstra's Algorithm
- Single pair shortest path using greedy method
- All Points Shortest path using Dynamic Programming
Unit 7 Backtracking
- General method
- n-queen problem
- Sum of subset problem
- Graph coloring problem
- Hamiltonian cycle problem
- Branch and Bound: General method
- LC branch and bound
- FIFO branch and bound
- Traveling salesman problem
Unit 8 Introduction to NP-Completeness
- The class P and NP, Polynomial reduction
- NP- Complete Problems
- NP-Hard Problems
- Approximation Algorithm: TSP Randomized Algorithm
- : Quick sort
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