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The aim of this course is to expose the students to the need to develop and employ an advanced sense of moral reasoning in accounting practice, notwithstanding the regulatory framework that directs practice. To this end, this course will address ethical issues pertaining to the practice of accounting auditing and accountability, such that students will be able to undertake such practices applying reasoning as Kolberg identifies being consistent with post-conventional moral development.

This course is not available to those taking a major or minor in chemistry and may not be used as a prerequisite for any other chemistry course. This course presents a broad-based introduction to modern chemistry for students not majoring in chemistry but who require a background in chemistry for other sciences. The topics covered include sections on physical chemistry(thermodynamics, kinetics, electro-chemistry and the properties); inorganic chemistry (atomic structure, periodicity, main group and transition metal chemistry) and organic chemistry (reactions and uses of important aliphatic and aromatic compounds). Wherever possible examples from applied sections will be used in this course.

This course is not available to those taking a major or minor in chemistry and may not be used as a prerequisite for any other chemistry course. This course presents a broad-based introduction to modern chemistry for students not majoring in chemistry but who require a background in chemistry for other sciences. The topics covered include sections on physical chemistry(thermodynamics, kinetics, electro-chemistry and the properties); inorganic chemistry (atomic structure, periodicity, main group and transition metal chemistry) and organic chemistry (reactions and uses of important aliphatic and aromatic compounds). Wherever possible examples from applied sections will be used in this course.

Cannot be credited with CS102. An introduction to computing programming language hierarchy (machine assembly, high-level) and basic computer organisation (i/o, main storage, secondary storage and CPU). Problem solving and algorithms using a modern high-level language; programme design; structured programming concepts; debugging, testing and documentation; and applications.

Cannot be credited with CS102. An introduction to computing programming language hierarchy (machine assembly, high-level) and basic computer organisation (i/o, main storage, secondary storage and CPU). Problem solving and algorithms using a modern high-level language; programme design; structured programming concepts; debugging, testing and documentation; and applications.

Cannot be credited with CS102. An introduction to computing programming language hierarchy (machine assembly, high-level) and basic computer organisation (i/o, main storage, secondary storage and CPU). Problem solving and algorithms using a modern high-level language; programme design; structured programming concepts; debugging, testing and documentation; and applications.

Cannot be credited with CS102. An introduction to computing programming language hierarchy (machine assembly, high-level) and basic computer organisation (i/o, main storage, secondary storage and CPU). Problem solving and algorithms using a modern high-level language; programme design; structured programming concepts; debugging, testing and documentation; and applications.

This course on algorithms addresses topics such as appropriate choice of data structures, sorting and searching algorithms, recursive algorithms, and complexity, and issues associated with computability and decidability. Analysis of algorithms includes order notation, recurrence equations, worst case and expected order statistics.

Artificial Intelligence (AI) is a broad field of study encompassing areas such as data mining, machine learning, robotics and pattern recognition. The real applications of AI is diverse, ranging from fuzzy-based control cooker, to filtering spam emails, to autonomous robots exploring martin terrain. The course will involve weekly readings of seminal and relevant research papers, paying particular attention to the alogrittms and key results. The discussions will include but not be limited to the following topics: Evolutionary computation, Neutral networks, Fuzzy logic, Machine learning. For this postgraduate course the students are expected to do independent research and present their findings.