Skip to main content
grasp.study
About
Explore
Pricing
Log in
Try it for free
Back to course
👋
Welcome to a Grasp lesson
Create a free account
to keep studying and create your own study path.
Gate Data Science and AI
·
Module 6
Algorithms: Sorting, Searching, and Design
1
Implementing and Analyzing Search Algorithms
Implement linear search and binary search algorithms and analyze their complexities.
2
Introduction to Bubble Sort and Insertion Sort
Implement and analyze simple sorting algorithms: bubble sort and insertion sort.
3
Advanced Sorting: Merge and Quick Sort
Implement and analyze advanced sorting algorithms: merge sort and quick sort.
4
Unlocking Dynamic Programming: Optimal Substructure & Overlapping Subproblems
Describe the principles of dynamic programming (optimal substructure, overlapping subproblems).
5
Fibonacci with Memoization and Tabulation
Solve the Fibonacci sequence problem using both memoization (top-down) and tabulation (bottom-up) DP.
6
Greedy Algorithms: Activity Selection
Describe the greedy algorithm paradigm and apply it to solve the Activity Selection problem.
7
Python Graph Representations
Implement graph representations (adjacency list, adjacency matrix) in Python.
8
Graph Traversal: BFS and DFS
Implement Breadth-First Search (BFS) and Depth-First Search (DFS) for graph traversal.
Previous module
Core Data Structures
Next module
Database Systems and SQL