This course is to build a preliminary foundation in spoken Chinese for the students within limited time and enable them to communicate in the target language for some basic functions. 250 most frequently used Chinese characters will also be taught. Meanwhile passing HSK 2 is an optional target. This course is also helpful to those who want to study Chinese language in depth in the future. No prerequisite is required. By completing this course, students will have a vocabulary size of 500 words and reach the proficiency level of HSK 2, and be able to communicate with Chinese people fluently in most topics. The course has the full support of a MOOC, and can be delivered in the “flipped classroom” mode, which is efficient for both face-to-face and distant learning. The MOOC has been certified as a “national high-quality undergraduate course” by the Ministry of Education of China.

CHN0902

This is a beginners' course. If you have learned Mandarin Chinese before, please contact the instructor ([email protected]) for suggestion.

Assessment:

• Attendance and participation in online classes: 20%
• Homework: 30%
• Mid-term Exam: 10%
• Final Exam: 40%

Course Introduction Video 
Please visit the website for more details.

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This course includes introduction to algorithm analysis and Big-Oh notation; fundamental data structures including priority queues, hash tables, binary trees, binary search trees, balanced trees, and graphs; searching and sorting algorithms; basic graph algorithms; and introduction to dynamic programming.

ECE2810J

Introduction to programming, Discrete Math/Computer Science/Junior.

Assessment:

• Participation: 5%
• In-class quizzes/Written assignments: 20%
• Programming assignments: 30%
• Midterm Exam: 20%
• Final Exam: 25%

Exact time for classes has not been decided yet, subject to change.

Course Introduction Video
Please visit the website for more details.

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The course will cover concepts and skills to tackle real-world data science problems. We will follow the data science life cycle to discuss data collection, data cleaning, data visualization, modeling, and data informed decision making. We will introduce concepts in probability, statistical inference, and machine learning. By working on real datasets, you will develop skills in programing and scientific computation (R and Python). In the course, you will learn how to build data-driven models from scratch to inform decision making.

ECE4710J

N/A

Assessment:

• Homework (5-7 submissions): 30%
• Project: 20%
• Midterm: 20%
• Final: 30%
  *Extra Credit: 3%

The exact time of classes has not been decided, subject to change.

Course Introduction Video
Please visit the website below for more details.

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This course builds on basic finance theory and economic principles to address topics that are important for managing financial institutions in a rapidly changing international environment. The students are expected to learn not only the theoretical framework to analyze the financial system, risk management and financial crisis, but also to learn how to apply tools and methods leant in this course to solve problems faced by the banks in the real economy. This course consists of following topics: Specialness, Risks and Regulations of Financial Institutions; Organization, Structure, Changing Dynamics of Banking Industry and Performance Evaluation of Commercial Banks; Liquidity Risk and Monetary Policy; Interest Rate Risk and Market Risk; Credit Risk.

ECON3515

3-4 year Students major in economics, finance, management. Students in other majors with solid background in mathematics, basic economics can apply with consent of lecture. 

Assessment:

• Final Exam: 40%
• Class Assignments: 30%
• Presentation and Term Paper: 20%
• Class Participation: 10%

Course Introduction Video
Please visit the website for more details.

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This course introduces advanced data structure such as different type of tree, Hash table and graph, some algorithm will also be revised. Data structure is one of the fundamental courses in Computer Science. It deals with storage and processing technique of data. The objective of the course is to master the following aspects: 1) Understand the logical relationship between data and processing requirements; 2) How to deal with data storage; 3) how to process data. The course will be divided into 5 parts: 1)  list, stack and Queue; 2) Binary Tree, Non-Binary Tree; 3) Sorting; 4) Searching: Hashing and other method; 5) Graph.

ICE3402P

Have C++ basis.

Assessment

• Assiduity：10%
• Homework: 50%
• Final Evaluation: 40% (Online Quiz 20%; Project + Report: 20%)

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The purpose of this course is to provide an introduction to Lie groups and Lie algebras. This course is divided into two parts taught every Spring semester. The first part presents the basic structure theory of complex semi-simple Lie algebras up to and including the classification by Dynkin diagrams. The second part presents the basic theory of Lie groups starting with elementary properties and going through the standard results up to and including Lie’s Third Theorem.

For the first part, a good knowledge of advanced linear algebra is needed. For the second part, familiarity with manifolds is advised but not necessary since it will be reviewed. The two parts are independent of each other. The basic reference books are Humphries “Introduction to Lie algebras and their representations”, Duistermaat and Kolk “Lie Groups”, Knapp “Lie groups, beyond an introduction”, plus other secondary sources that could serve for additional reading, depending on the tine interests of the students. Depending on the background and interest of the students, the material of the course can emphasize certain topics.

Lie theory is basic to most areas of mathematics, physics, and engineering. The goal is to familiarize the students with this theory so that they can use Lie theory in their own course work and research. In this class, Professor could answer students’ questions in 6 languages: English, German, French, Spanish, Portuguese, Romanian.

MATH4405

Advanced undergraduate mathematical analysis.
Fimilarity with calculas om mainfolds is helpful but not essential.

Assessment:

• 100% Final Report

Course Introduction Video
Please visit the website for more details.

N/A

The course will cover concepts and skills to tackle real-world data science problems. We will follow the data science life cycle to discuss data collection, data cleaning, data visualization, modeling, and data informed decision making. We will introduce concepts in probability, statistical inference, and machine learning. By working on real datasets, you will develop skills in programing and scientific computation (R and Python). In the course, you will learn how to build data-driven models from scratch to inform decision making.

ME2110J

N/A

Assessment:

• Homework (5-7 submissions): 30%
• Project: 20%
• Midterm: 20%
• Final: 30%
  * Extra Credit: 3%

Course Introduction Video
Please visit the website for more details.

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Materials chemistry is the study of the synthesis, structure, properties, and application of solid materials. Our technology-driven world is fuelled by advances in materials chemistry with examples of application in areas such as microelectronics, polymers, and energy technology. This course introduces the materials chemistry of several major categories of materials (metals, ceramics and glasses, semiconductors, polymers, nanomaterials) with the emphasis of materials synthesis. The topics span from traditional extractive metallurgy to more recent development of nanomaterials and biomaterials.

MSE2602

Sophomore with major in Materials Science.

Assessment:

• Homework 15%
• Quiz 15%
• Class participation 10%
• Midterm 10%
• Final Exam 50%

Course Introduction Video
Please visit the website for more details.

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Materials are the physical foundations for the development of science and technology. The human civilizations are historically designated by the evolution of materials, such as the Stone Age, the Bronze Age and the Iron Age. Nowadays, materials science and technology support most of the industrial sectors, including aerospace, telecommunications, transportation, architecture, infrastructure and so on. Fundamentals of Materials Science is a core module for undergraduates majored in materials science and engineering. 

An integrated approach of combining metallic, ceramic and polymeric materials will be adopted in this course, for the attendants to attain a deep understanding on the correlation of composition, microstructure, processing and properties in materials science. The first part of this course will cover atomic bonding, structure of solids, defects, and mechanical properties of materials. 

MSE2606

For materials science & metallurgy students. Prerequisites include calculus, college physics, and thermodynamics.

Assessment:

• Class participation and quizes: 10%
• Problem sets: 10%
• Experiments (for offline students) / Mini research report (for online students): 20%
• Final exam: 60%

Course Introduction Video
Please visit the website for more details.

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As nations bind together to tackle global climate change, one of the urgent needs is the energy sector’s transition from being fossil-fuel reliant to embracing sustainable carbon-free solutions. Through a multi-national collaboration, this course aims to introduce a redefined perspective of fuel utilisation for the power and transportation sectors, placing emphasis on alternative fuels derived from renewable resources that are essential contributors to the goals of carbon neutrality.

Some of the low or zero-carbon fuels such as hydrogen, ammonia, biofuels and emerging low carbon fuels adaptable to current or new energy systems will be explored in the context of production, utilisation, economics and sustainability. The impacts of future fuels on the environment, resource availability and social well-being need to be holistically considered and supported by diverse solutions, in alignment with the Sustainable Development Goals of Affordable and Clean Energy (SDG 7) and other related SDGs as put forth by the United Nations. From this course, the students will grasp the broad concept of alternative fuel production, application and challenges faced in moving towards a net zero-carbon society.

PJ187

N/A

Assessment:

• Attendance: 20%
• Assignments: 40%
• Presentation: 40% 

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