Classes

Data and Knowledge Modeling and Analysis

Semester: 

Winter

Offered: 

2024

Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments,

databases, computer files, or the Internet, there is a dire need for effective methods to model and

analyze the data and extract useful knowledge and information from it. This course aims to provide

engineering graduate students with essential knowledge of data representation, grouping, mining and

knowledge discovery.

Read more about Data and Knowledge Modeling and Analysis

Co-operative and Adaptive Algorithms

Semester: 

Spring

Offered: 

2023

There are many computational problems in our real life that are computable within a reasonable amount of time using a reasonable computing device. For this type of problems, we seek algorithms that can deterministically search for optimal solutions in reasonable time. On the other hand, there are problems that are hard, if not impossible, to compute, or complex enough to the extent that deterministic methods take too long to find solutions- even approximate solutions. Some of these problems are ill-conditioned, in the sense that a small change in the independent variables (inputs) causes...

Read more about Co-operative and Adaptive Algorithms

Tools of Intelligent Systems Design

Semester: 

Spring

Offered: 

2023
Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of... Read more about Tools of Intelligent Systems Design

Fundamentals of Computational Intelligence

Semester: 

Winter

Offered: 

2022
The course discusses fundamentals and recent advances made in the field of computational
intelligence. The course focuses on highlighting the latest tools of machine learning and
approximate reasoning for building accurate models based either on collected data or past
experiential knowledge stored in the form of rules base. The course covers fundamental aspects
of machine learning for building model prediction and powerful classifiers. It highlights concepts
in supervised and... Read more about Fundamentals of Computational Intelligence

Tools of Intelligent Systems Design

Semester: 

Spring

Offered: 

2022
Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of... Read more about Tools of Intelligent Systems Design

Tools of Intelligent Systems Design

Semester: 

Spring

Offered: 

2021
Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of... Read more about Tools of Intelligent Systems Design

Data & Knowledge Modelling & Analysis

Semester: 

Spring

Offered: 

2020

Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.

Read more about Data & Knowledge Modelling & Analysis

Tools of Intelligent Systems Design

Semester: 

Spring

Offered: 

2020
Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of... Read more about Tools of Intelligent Systems Design

Data & Knowledge Modelling & Analysis

Semester: 

Winter

Offered: 

2019

Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.

Read more about Data & Knowledge Modelling & Analysis

Tools of Intelligent Systems Design

Semester: 

Spring

Offered: 

2019
Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of... Read more about Tools of Intelligent Systems Design