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KE5207
COMPUTATIONAL INTELLIGENCE II
2018/2019, Semester 1
Non-Faculty-Based Departments (Institute Of Systems Science)
Modular Credits: 3
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Learning Outcomes
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The aim of this elective course of the Master of Technology (MTech) in Knowledge Engineering (KE) is to introduce Fuzzy Systems, Rough Sets, Bayesian Nets and Evolutionary Computation and their role in the development of intelligent systems for Business Analytics The objectives of the course are to: (1) Introduce computational intelligence techniques with a focus on Fuzzy Systems, Rough Sets, Bayesian Nets and Evolutionary Computation. (2) Explore how these techniques can be used to construct intelligent systems to solve real-world problems such as reasoning, decision making and optimization.
Workload
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1.0-0.5-0.5-3.0-2.0
Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week