This course aims to develop your knowledge, understanding and skills about algorithm design and analysis. Upon the successful completion of this course, students shall be able to
- apply additional analysis techniques in complexity analysis of recursive algorithms
- apply, design and analyse algorithms using a number of approaches to solve various problems like sorting, shortest-path, minimum spanning tree, optimal sequencing for matrix multiplication, the longest common subsequence, string matching. Students will also learn the concepts of complexity classes P & NP and apply greedy heuristic approach to solve NP-complete problems.
Total hours per week: 3 hrs
| AUs | 3.0 AUs |
| Grade Type | |
| Prerequisite | Must be a Turing AI Scholar SC1303 |
| Exam |
Prerequisite Graph
Required first
No prerequisite
SC2301
Algorithm Design & Analysis
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 1330 | 10418 SEM (TAIS1) 1330-1620 Wed TAISPSPACE | ||||
| 1400 | |||||
| 1430 | |||||
| 1500 | |||||
| 1530 | |||||
| 1600 |
Other Relevant Mods
SC1001
Introduction To Computational Thinking & Programming
SC1004
Linear Algebra For Computing
SC1005
Digital Logic
SC1006
Computer Organisation & Architecture
SC1007
Data Structures & Algorithms
SC1008
C & C++ Programming
SC1013
Physics For Computing
SC1123
Math 1: Linear Algebra & Calculus For Computing
SC1301
Language & Logic