Category: NTU Mathematical Sciences

Mathematical Sciences is a broad term encompassing the disciplines of Pure Mathematics, Applied and Computational Mathematics, and Statistics, as well as subfields of computer science, engineering, life sciences, physical sciences, and social sciences.

The Division of Mathematical Sciences offers a variety of four-year undergraduate degree programmes suitable for students interested in different aspects of the mathematics and its applications.

Our programmes begin with common core courses covering the fundamental topics of mathematics, including calculus, linear algebra, discrete mathematics, probability, scientific programming, and mathematical exposition. Our students then have the opportunity to take various advances courses in Pure Mathematics, Applied Mathematics, Statistics, and Business Analytics.

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In today’s business, data analysis plays an important role in making decisions more scientific and helping the business achieve effective operation. By closely examining data we can find patterns to perceive information, and the information can be used to enhance knowledge. This course provides basic concepts for data analysis with the usage of the R programming language. You will learn the skills of plotting, summarising, making inferences, and presenting various types of data.

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This course aims to develop your understanding/grasping of the regression models of summarizing the relationship among variables. Linear regression models are widely used today in business, administration, economics, engineering, and the social, health and biological sciences. You should learn the rigorous way to approach regression models and be able to build regression models for real data.

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This course aims to develop your understanding of the statistical concepts of parameter estimation and hypothesis testing that are fundamental for real life applications of statistics as well as for numerous further courses in the curriculum of the statistics track.

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With the development of digitalization, algorithms have become more and more pervasive in our lives, and this trend is likely to accelerate in the future. Almost all industries are now widely embracing the possibilities offered by efficient algorithms. How can companies with a huge amount of data search in their database? How can your map application find the shortest path from your location to a certain destination? How can Internet packets be routed to maximize the efficiency of the network? How can you render electricity distribution more efficient? How booking websites manage to find for you the best hotels according to several criterions? Etc.

The aim of this course is to show you some crucial algorithmic paradigms, while using strong connections to real-world applications as examples. This will allow you to learn new problem-solving techniques and very important algorithms, while developing your general knowledge in where and how algorithms are actually used in real-world applications.

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Building on Calculus, Linear Algebra, and Algorithms and Computing course sequences, this course aims to equip you with technical knowledge of the theory of ordinary differential questions and communication skills required to work as a team on modelling a real life phenomenon with a system of ordinary differential equations.

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This is the first of two courses on real analysis. This course is compulsory for students of mathematical sciences, and it is a prescribed elective course for students from other schools as well. The course aims to present a careful treatment of the principal topics of calculus I and Calculus II, such as real numbers, basic topology of the real line, sequences and series of numbers and of functions, and to illustrate the power of the subject through a variety of applications. After learning this course, you will be able to understand better many results from Calculus I and II which you studied without proofs.

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This is a core mathematical course, aiming to develop your understanding of fundamental concepts in probability and statistics such as random variables, independence, basic probability distributions, and confidence intervals. The course also prepares you for further statistics courses such as MH3500 in the Statistics Track.

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Application of computing skills and previously-learnt mathematical topics (Linear Algebra, Calculus, Discrete Mathematics, etc.) for solving real-world problems. This course emphasizes group project work, and assessments are based substantially on a term project.

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This core MAS course aims to introduce group theory as an abstraction of planar isometries and structures that is essential for more advance algebra courses and applications. The axiomatic concepts serve as a language to study concrete examples in broader sense and helps in developing logical thinking.

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