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CSE6413: Network Science
Course Details: Introduction to Network Science: networks behind complex systems, characteristics of network science, societal and scientific impact of network science; Graph theoretic fundamentals: adjacency and adjacency representations, degree and degree sequence, paths and distance on a graph, center and diameter of a graph, Euler tours and Hamiltonian cycles, connectivity, graph drawing;Network properties: degree distribution, degree correlations, distance statistics, centrality, clustering coefficient, small-world effect, robustness; Network models and evolving networks: random networks, scale-free networks, Barabási–Albert (BA) model, Bose-Einstein condensation; Communities: clustering, modularity, overlapping communities, testing and characterizing communities; Network robustness: percolation theory, robustness of scale-free networks, attack tolerance, cascading failures, designing robust networks; Spreading phenomena: network epidemics, contact networks, immunization, epidemic prediction.
Ph.D. in Computer Science and Engineering
Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh
COM760: Autonomic Computing and Robotics
Course Details: This module provides an overview of smart robotics and AI. It is designed to provide students with a strong foundation through the core topics and the key technologies of robotics and AI while providing hands-on experience on programming smart robots in the labs. The module will explore practically coding AI techniques for Robotics and the focus is given to design and implement smart robots exhibiting AI behaviours.
M.Sc. in Computer Science (MSc CS)
University of Ulster, Belfast, Northern Ireland, UK
COM745: Big Data and lnfrastructure
Course Details: Within this module a variety of database and data storage paradigms will be explored, ranging from more traditional relational systems to NoSql and object stores, time series databases, semantic store and graph stores. Consideration will be given to big data and the problem with storing and querying high volumes of highly variable data which is stored and processed at a high speed. The cloud computing paradigm will also be introduced and how to avail of its power and resources. The core concepts of distributed computing will be examined in the context of a data lake. Students will be taught, practically and theoretically, about the components of Data lakes, workflows, functional programming concepts, use of MapReduce, Spark, Pig, and Hive.
M.Sc. in Computer Science (MSc CS)
University of Ulster, Belfast, Northern Ireland, UK
COM747: StatisticaI Modeling and Data Mining
Course Details: Applied regression analysis, with emphasis on general linear model (e.g., multiple regression) and generalized linear model (e.g., logistic regression). Special attention to modern extensions of regression, including regression diagnostics, graphical procedures, and bootstrapping for statistical influence. P/NP or letter grading.
M.Sc. in Computer Science (MSc CS)
University of Ulster, Belfast, Northern Ireland, UK
COM761: Machine Learning
Course Details: This module provides an overview of Data Science process/pipeline. It provides systematic understanding of mathematical and statistical knowledge for explorable data analysis (EDA) and to understand the foundations of supervised and unsupervised machine learning algorithms, and with the practical programming skills to apply them to real world datasets. The module discusses the constraints that needs to be considered when designing, implementing, evaluating and visualising solutions to real-world complex problems.
M.Sc. in Computer Science (MSc CS)
University of Ulster, Belfast, Northern Ireland, UK
COM762: Deep Learning and lts Application
Course Details: This course covers the fundamental principles, practical applications, and advanced techniques of Deep Learning. Through a combination of lectures, hands-on exercises, and real-world case studies, students will gain a solid understanding of neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other deep learning architectures with a particular focus on supervised Deep Learning and reasonable coverage of unsupervised methods. Lectures are supplemented by assignments and lab tasks using Python programming language. Emphasising theoretical concepts and practical implementation, this course aims to equip students with the knowledge and skills to tackle complex problems in artificial intelligence and data analysis using deep learning.
M.Sc. in Computer Science (MSc CS)
University of Ulster, Belfast, Northern Ireland, UK
COM769: Scalable Advanced Software Sotutions
Course Details: This module aims to explore a range of modern development and deployment concepts in the context of scalable and high-performance computing services. Within this module concepts such as containerisation, Continuous Integration, Continuous Delivery, cloud architectures, scalable solutions and infrastructure will be explored. Additionally, advanced programming/development concepts facilitating high performance solution development will be examined.
M.Sc. in Computer Science (MSc CS)
University of Ulster, Belfast, Northern Ireland, UK
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