Discipline ID
97ac1514-598d-4ae9-af20-fdf75b940953
COURSE DETAIL
OPTIMIZATION
Country
France
Host Institution
University of Bordeaux
Program(s)
University of Bordeaux
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
115
UCEAP Course Suffix
UCEAP Official Title
OPTIMIZATION
UCEAP Transcript Title
OPTIMIZATION
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
The objective of this course is to initiate the understanding of the methods and models of optimization. The first part of the course concerns convex optimizations, specifically conditions of optimality, the algorithm of the gradient, and its variants. The second part of the course concerns linear programming in the real and natural numbers. The emphasis is put on modeling. Topics include: modeling, the formalization of concrete problems in the form of mathematical optimization; optimization without constraints (analytic resolution, dichotomy, variants of the gradient); optimization with constraints (conditions of optimality, linear programming, linear programming with whole numbers).
Language(s) of Instruction
French
Host Institution Course Number
4TMQP01U
Host Institution Course Title
OPTIMIZATION
Host Institution Campus
UNIVERSITÉ DE BORDEAUX: Collège des Sciences et Techniques
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathématiques
COURSE DETAIL
UNDERGRADUATE INDEPENDENT RESEARCH
Country
Hong Kong
Host Institution
Chinese University of Hong Kong
Program(s)
Research in Hong Kong
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Statistics
Sociology
Psychology
Political Science
Physics
Mathematics
Linguistics
Legal Studies
International Studies
History
Health Sciences
Geography
Environmental Studies
English
Engineering
Education
Economics
Earth & Space Sciences
Computer Science
Biological Sciences
UCEAP Course Number
186
UCEAP Course Suffix
S
UCEAP Official Title
UNDERGRADUATE INDEPENDENT RESEARCH
UCEAP Transcript Title
RESEARCH
UCEAP Quarter Units
9.00
UCEAP Semester Units
6.00
Course Description
The undergraduate research program places students in research opportunites to conduct indpendent research under the supervision of a Chinese University of Hong Kong faculty. Students are expected to spend approximately 15 to 20 hours per week in independent research as well as attend lectures and labs.
Language(s) of Instruction
English
Host Institution Course Number
IASP4091
Host Institution Course Title
UNDERGRADUATE INDEPENDENT RESEARCH
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
COURSE DETAIL
GRAPHS AND NETWORKS
Country
Ireland
Host Institution
University College Dublin
Program(s)
University College Dublin
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
111
UCEAP Course Suffix
UCEAP Official Title
GRAPHS AND NETWORKS
UCEAP Transcript Title
GRAPHS & NETWORKS
UCEAP Quarter Units
4.00
UCEAP Semester Units
2.70
Course Description
This course prepares students for essentials needed in various fields of discrete mathematics and computer science. It covers concepts and results in graph theory and the theory of network flows.
Language(s) of Instruction
English
Host Institution Course Number
MATH20150
Host Institution Course Title
GRAPHS AND NETWORKS
Host Institution Campus
UC Dublin
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematics
COURSE DETAIL
MODERN ALGEBRA
Country
Taiwan
Host Institution
National Taiwan University
Program(s)
National Taiwan University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
142
UCEAP Course Suffix
B
UCEAP Official Title
MODERN ALGEBRA
UCEAP Transcript Title
MODERN ALGEBRA
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description
This course studies fundamentals in algebra. Topics include field theory, dedekind domains, finite group representations, and lie algebras.
Language(s) of Instruction
Chinese
Host Institution Course Number
MATH5002
Host Institution Course Title
MODERN ALGEBRA
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
COURSE DETAIL
NUMERICAL ANALYSIS II
Country
Ireland
Host Institution
University of Galway
Program(s)
Irish Universities,National University of Ireland, Galway,University of Galway
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
115
UCEAP Course Suffix
UCEAP Official Title
NUMERICAL ANALYSIS II
UCEAP Transcript Title
NUM ANALYSIS 2
UCEAP Quarter Units
4.00
UCEAP Semester Units
2.70
Course Description
This course explores polynomial interpolation and its applications in numerical integration, numerical differentiation, splines, and finite element methods for ODEs as well as implementation of methods.
Language(s) of Instruction
English
Host Institution Course Number
MA378
Host Institution Course Title
NUMERICAL ANALYSIS II
Host Institution Campus
National University of Ireland, Galway
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematics
COURSE DETAIL
NUMERICAL ANALYSIS- BASIC COURSE
Country
Sweden
Host Institution
Lund University
Program(s)
Lund University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
122
UCEAP Course Suffix
UCEAP Official Title
NUMERICAL ANALYSIS- BASIC COURSE
UCEAP Transcript Title
NUMERCL ANLYS BASIC
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course teaches basic computational methods for solving simple and common mathematical problems through computers and numerical software. This includes the construction, application, and analysis of basic computational algorithms. Mathematical models are often written as systems of linear and nonlinear equations and differential equations. Students discretize such equations by constructing computable approximations, and are expected to implement and apply such algorithms independently.
Language(s) of Instruction
English
Host Institution Course Number
NUMA41
Host Institution Course Title
NUMERICAL ANALYSIS- BASIC COURSE
Host Institution Campus
Host Institution Faculty
Science
Host Institution Degree
Host Institution Department
Mathematics
COURSE DETAIL
FUNCTIONAL ANALYSIS
Country
Denmark
Host Institution
University of Copenhagen
Program(s)
University of Copenhagen
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
144
UCEAP Course Suffix
UCEAP Official Title
FUNCTIONAL ANALYSIS
UCEAP Transcript Title
FUNCTIONAL ANALYSIS
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course covers a number of fundamental topics within the area of Functional Analysis. These topics include: Banach spaces, the Hahn-Banach theorem, including its versions as separation theorem, weak and weak* topologies, the Banach-Alaoglu theorem, fundamental results connected to the Baire Category theory (the open mapping theorem, the closed graph theorem and the Uniform Boundedness Principle), as well as and convexity topics, including the Krein-Milman theorem and the Markov-Kakutani fixed point theorem; Operators on Hilbert spaces, Spectral theorem for self-adjoint compact operators; Fourier transform on R^n and the Plancherel Theorem; Radon measures and the Riesz representation theorem for positive linear functionals.
Language(s) of Instruction
English
Host Institution Course Number
NMAK10008U
Host Institution Course Title
FUNCTIONAL ANALYSIS
Host Institution Campus
Science
Host Institution Faculty
Host Institution Degree
Host Institution Department
Mathematical Sciences
COURSE DETAIL
FLUID MECHANISMS
Country
United Kingdom - England
Host Institution
University of Manchester
Program(s)
University of Manchester
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
UCEAP Course Number
119
UCEAP Course Suffix
UCEAP Official Title
FLUID MECHANISMS
UCEAP Transcript Title
FLUID MECHANICS
UCEAP Quarter Units
4.00
UCEAP Semester Units
2.70
Course Description
This course introduces continuum mechanics in general and theoretical fluid mechanics in particular. Fluid mechanics predicts the properties (pressure, density, velocity etc.) of liquids and gases under external forces. Examples of studied liquids include water, blood, and air. Of the many diverse fields where an understanding of the motion of fluids is important, one can mention oceanography and meteorology (in particular the dynamics of ocean circulation and weather forecasting), biological fluid dynamics (for example, blood flows through arteries), and aerodynamics.
Language(s) of Instruction
English
Host Institution Course Number
MATH20502
Host Institution Course Title
FLUID MECHANISMS
Host Institution Campus
University of Manchester
Host Institution Faculty
Host Institution Degree
Host Institution Department
School of Mathematics
COURSE DETAIL
OPTIMIZATION
Country
Sweden
Host Institution
Lund University
Program(s)
Lund University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
Engineering
UCEAP Course Number
125
UCEAP Course Suffix
UCEAP Official Title
OPTIMIZATION
UCEAP Transcript Title
OPTIMIZATION
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
The course presents basic optimization theory, and gives an overview of the most important methods and their practical use.
Language(s) of Instruction
English
Host Institution Course Number
FMAN61
Host Institution Course Title
OPTIMIZATION
Host Institution Campus
Lund
Host Institution Faculty
Engineering
Host Institution Degree
Host Institution Department
Mathematical Sciences
COURSE DETAIL
MATHEMATICS FOR MACHINE LEARNING
Country
United Kingdom - England
Host Institution
Imperial College London
Program(s)
Imperial College London
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Mathematics
Computer Science
UCEAP Course Number
183
UCEAP Course Suffix
UCEAP Official Title
MATHEMATICS FOR MACHINE LEARNING
UCEAP Transcript Title
MATH MACHINE LEARN
UCEAP Quarter Units
5.00
UCEAP Semester Units
3.30
Course Description
In this class you will have the opportunity to be provided with the necessary mathematical background and skills in order to understand, design and implement modern statistical machine learning methodologies, as well as inference mechanisms. You will be provided with examples regarding the use of mathematical tools for the design of foundational machine learning and inference methodologies, such as Principal Component Analysis (PCA), Bayesian Linear Regression and Support Vector Machines Learning outcomes Upon successful completion of this module you will be able to implement foundational machine learning algorithms from scratch. Students will be able to apply appropriate mathematical techniques in a machine learning setting and critically assess the quality of machine learning models, as well as evaluate connections between different machine learning algorithms.
Language(s) of Instruction
English
Host Institution Course Number
CO496
Host Institution Course Title
MATHEMATICS FOR MACHINE LEARNING
Host Institution Campus
Imperial
Host Institution Faculty
Host Institution Degree
Host Institution Department
Computing