[vc_row el_class=”inner-body-content” css=”.vc_custom_1666760344939{padding-top: 30px !important;padding-bottom: 20px !important;}”][vc_column][vc_custom_heading text=”COURSE OBJECTIVES” use_theme_fonts=”yes” css=”.vc_custom_1666760326785{margin-top: 0px !important;}”][vc_column_text]
- Reproduce design of algorithms using different algorithms design techniques i.e. Brute Force, Divide & Conquer, Dynamic Programming, Greedy Algorithms & Backtracking, Branch & Bound.
- Analyze the time and space complexity of different algorithms by using standard analysis techniques
- Implement the algorithms, compare the implementations empirically.
[/vc_column_text][vc_custom_heading text=”COURSE LEARNING OUTCOMES (CLO)” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]CLO: 1. Reproduce design of algorithms using different algorithms design techniques
CLO: 2. Analyze the time and space complexity of different algorithms
CLO: 3. Implement the algorithms, compare the implementations empirically
[/vc_column_text][vc_custom_heading text=”COURSE CONTENTS” use_theme_fonts=”yes”][vc_column_text css=”.vc_custom_1666760307044{margin-bottom: 0px !important;}”]
- Introduction to Algorithms and its applications,Time Complexity of an algorithm
- Asymptotic notation of an algorithm. Big Oh (O) and Big theta etc,Asymptotic Notation with Examples
- Analyzing Time Complexity of an Algorithm, Analysis of Recursive algorithm
- Fibnoci Sequence and its Running time, Brute Force and Selection sort algorithm
- Bubble Sort Algorithm and its time complexity, Brute-force String matching algorithm and its complexity
- Travelling Salesman Problem and Knapsack Problem, BFS and DFS traversal of Graphs
- Insertion Sort and Revision of Topics, Divide and Conquer Approach (Quick Sort)
- Quicksort and its complexity, Revision of Topics
- Decrease and Conquer Approach , Merge Sort and its complexity
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