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.
Software Engineering Fundamentals
·
Module 1
Data Structures & Algorithms Fundamentals
1
Big-O Notation: Analyzing Algorithm Complexity
Analyze time and space complexity of algorithms using Big-O notation.
2
Data Structure Trade-Offs: Arrays, Linked Lists, and Hash Maps
Compare trade-offs of arrays, linked lists, and hash maps to solve a given problem.
3
Trees, Heaps, and Graphs: A Comparative Study
Compare trade-offs of trees (BST), heaps, and graphs to solve a given problem.
4
Merge Sort: Implementation and Complexity Analysis
Implement merge sort and analyze its time and space complexity.
5
Quicksort vs. Mergesort: Implementation & Trade-offs
Implement quicksort and compare its practical trade-offs with merge sort.
6
Graph Traversal with BFS and DFS
Solve graph traversal problems using Breadth-First Search (BFS) and Depth-First Search (DFS).
7
Dynamic Programming: 0/1 Knapsack Problem
Solve the 0/1 knapsack problem using dynamic programming.
8
Choosing Data Structures and Algorithms
Select the most appropriate data structure and algorithm for a given problem scenario and justify the choice.
Previous module
Next module
OS: Processes, Threads, and Scheduling