Computer Science

The course covers cryptology, web applications security, server security, client security, remote login, Email and spam, and DNS Security. A selection of the following topics is also included: E-cash overview: Blind signatures, blockchain technologies and digital monies, Bitcoin, Ethereum, smart contracts; Secure communication: TLS attacks; Database security: Inference, differential privacy; and anonymity: traffic analysis, Chaum's Mix, Tor.

This course covers processing principles of data types other than text format that are used to create multimedia contents like three dimensional solid body with various tools for the multimedia. 

The course covers the following topics:

• 3DCG
• Stereoscopic 3D
• 360degree video
• Gmae engine (Unity, UnrealEngine)

The course introduces the basic concepts in search and knowledge representation as well as several sub-areas of artificial intelligence. It focuses on covering the essential concepts in AI. The course covers Turing test, blind search, iterative deepening, production systems, heuristic search, A* algorithm, minimax and alpha-beta procedures, predicate and first-order logic, resolution refutation, non-monotonic reasoning, assumption-based truth maintenance systems, inheritance hierarchies, the frame problem, certainly factors, Bayes' rule, frames and semantic nets, planning, learning, natural language, vision, and expert systems and LISP.

This course establishes the foundation of a wide range of statistical learning methods. It aims to understand and utilize the fundamentals of various statistical learning models. 

The course covers:

• statistical learning;
• classical linear methods for regression and classification; 
• cross-validation;
• bootstrap; 
• modern linear methods;
• nonlinear methods; 
• tree-based methods;
• support vector machines;
• unsupervised learning;
• neural networks, and
• deep learning. 

These topics are the basics of statistical learning, but the core of machine learning. By the end of this course, students will have easier access to and understanding of deep learning and artificial intelligence.

The course requires the following prerequisites: 

• Python Basic – this course assumes a basic knowledge of Python
• STAT 241: Matrix Theory or Linear Algebra - provides a computational foundation for understanding statistical models.
• STAT 232: Mathematical Statistics- knowledge of probability theory and asymptotic evaluations. 

This course introduces information technologies (IT) in organizations and the interplay between IT, work, management, and organizations. The course examines the impacts of modern IT and the related artificial intelligence (AI) technologies on knowledge workers, teamwork, work design, management practices, and the organization. The course discusses the multifaceted roles IT can play to support communication, collaboration, and organizational improvements in operations, planning, and decision making. Students learn to apply strategic thinking to identify opportunities for IT-enabled innovations and issues involving information systems (IS) adoption and deployment.

This course aims to: 

• Understand the genesis of Big Data Systems 

• Understand practical knowledge of Big Data Analysis using Hive, Sqoop, Linux Shell  

• Provide the student with a detailed understanding of effective behavioral and technical techniques in Cloud Computing on Big Data  

• Demonstrate knowledge of Big Data in industry and its Architecture   

• Learn data analysis, modeling and visualization in Big Data systems 

Prerequisites: 

• Mastery over Microsoft Windows and its File Management (Windows Explorer) facilities  

• Basic knowledge of any programming language (SQL, Python, Java)  

• Basic knowledge of BI tools such as Excel, Tableau, Power BI, Google Spread Sheet 

This course offers a study of the theory of automata and formal languages. Topics include: automata theory; finite automata; languages and formal grammars; regular languages; pushdown automata; Turing machine; computational complexity.

In this course, students learn the fundamentals of spatial information, spatial querying, spatial information systems, and geometric problems involved in a spatial information system. They learn details about the spatial data formats (raster and vector), spatial relations (with particular emphasis on topological relations), spatial data structures, digital terrain modelling, geometric problems arising in spatial information systems, and algorithms to solve them. They develop a critical understanding of the different approaches to storing and manipulating spatial data: the loosely coupled approach of classical GIS versus the integrated approach of spatial database management systems. Students also analyze the Oracle Spatial object-relational model for storing and indexing spatial data. These notions complement their knowledge of other types of information systems seen in other computer science courses.

This course gives a practical introduction to system software, the interface between user applications and the operating system. The course covers system programming and operating system concepts, particularly process management, memory management, file systems and I/O, network programming, concurrent programming, and synchronization. The contents of the lecture are applied in labs and homework assignments. 

Prerequisite: Computer Architecture; Familiarity with C programming required or to be acquired through this course. 

This course examines the processes, methods, techniques and tools that organizations use to determine how they should conduct their business, with a particular focus on how web-based technologies can most effectively contribute to the way business is organized. It covers a systematic methodology for analyzing a business problem or opportunity, determining what role, if any, web-based technologies can play in addressing the business need, articulating business requirements for the technology solution, specifying alternative approaches to acquiring the technology capabilities needed to address the business requirements, and specifying the requirements for the information systems solution in particular, in-house development, development from third-party providers, or purchased commercial-off-the-shelf (COTS) packages.