CS2402 - Introduction to Computational Probability Modeling | ||||||||||||
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* 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 |