Data Science and Artificial Intelligence

Code	Course	Number of Credits	Description/Course Objective
AT82.01	Computer Programming for Data Science and Artificial Intelligence	2	The course objective is to provide students hands-on programming skills and best practices related to Data Science and Artificial Intelligence. It is a laboratory course in which students will develop programming skills in loading, cleansing, transforming, modeling and visualizing data.
AT82.02	Data Modeling and Management	3	The course emphasizes on emerging data models and technologies suitable for managing different types and characteristics of data. Students will develop skills in analyzing, evaluating, modeling and developing database applications with concerns on both technical and business requirements.
AT82.03	Machine Learning	3	The course provides students from a variety of science, engineering, and management backgrounds with a strong foundation in the fundamentals of machine learning and prepares them to perform R&D involving machine learning techniques and applications.
AT82.04	Business Intelligence and Analytics	3	This course will give students an understanding of the principles and practices of business intelligence and data analytics to support organizations in conducting their business in a competitive environment, in order to support better business decision making and capture new business opportunities.
AT82.05	Artificial Intelligence: Natural Language Understanding	3	Introducing students to the linguistic knowledge of natural languages together with the algorithms and technologies for processing them. Key linguistic concepts of words, morphology, parts-of-speech, syntax and semantics are presented together with algorithms and technologies like regular expressions, finite automata, context-free grammars, unification, first-order logic, lambda-notations, hidden Markov models as well as other rule-based or statistical algorithms.
AT82.06	Artificial Intelligence: Problem Solving and Planning	3	The course aims to introducing the students for the fundamentals of Artificial Intelligence and its techniques. Students will be exposed to several techniques on planning and decision procedures ranging from precise to uncertain and temporal reasoning with applications to intelligent agents.
AT82.07	Artificial Intelligence: Knowledge Representation and Reasoning	3	The course introduces students to the theories and methodologies of knowledge representation and reasoning in AI. Both the model and proof theoretic semantics of first-order logics (FOL) are presented. Examples and reasons for the weakness of FOL for practical reasoning are explained. Bayesian reasoning as an important tool in modelling uncertain reasoning is studied. Temporal reasoning, planning together with causal reasoning are presented. A new novel insight of practical reasoning as arguing is finally introduced together with theories of argumentation as a platform for modelling the arguing process. At last, application of practical reasoning in knowledge engineering is presented.
AT82.08	Computer Vision	3	The course provides students with research and development skills in the image processing, geometry, and statistical inference tools necessary for extracting useful information about the world from two-dimensional images, including applications to robot vision, intelligent video surveillance and monitoring, optical character recognition, and human-computer interfaces.
AT82.09	Human-Computer Interaction and Information Visualization	3	The objective of this course is to provide the concepts of HCI and user interfaces, focusing on user interface design and technologies. The students will learn principles and skills for designing interactive systems and Web-based applications.
AT82.10	Recent Trends in Machine Learning	3	The course builds on the content of Machine Learning, providing students with a deeper understanding of machine learning techniques and a wider variety of extant learning models. Students will be prepared to develop advanced machine learning applications and perform research at a state-of-the-art level.
AT82.11	Multicriteria Optimization and Decision Analysis	3	Multicriteria optimization and decision analysis deals with various aspects of finding optimal solutions in problems with multiple decision alternatives and conflicting objectives. This course will provide students an understanding of the decision making process and multicriteria decision analysis methods and optimization processes.
AT82.12	Software Development and Project Management	3	The course emphasizes modern and important software development, software processes, and project management. Student will tailor the software development process and project management for DS&AI projects, including planning, iterative development, test driven development, continuous integration/continuous delivery, versioning, and deliverables. The course provides examples and cases of how to apply the knowledge to the problems in DS&AI domains.