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CS2402 - Introduction to Computational Probability Modeling

Offering Academic Unit
Department of Computer Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
Equivalent Course(s)
Course Offering Term*:
Semester B 2020/21
Semester B 2021/22 (Tentative)

* The offering term is subject to change without prior notice
 
Course Aims

Due to the inherent uncertainty in the world, probability and statistics are used in many areas of computer science, such as data science, artificial intelligence, bioinformatics, networking, algorithms, and software testing.  In this course, students will learn concepts for computational modeling of random phenomenon, probability, and statistical inference. Students will write computer programs to simulate random phenomenon and analyze real-world data with computational probability models.


Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 50%
Examination: 50%
Examination Duration: 2 hours
^ For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.
 
Detailed Course Information

CS2402.pdf

Useful Links

Department of Computer Science