ACIT4010 Enterprise Networking: Practices and Technologies Course description

This course gives students hands-on experience in the design, configuration and troubleshooting of networks. This course is rooted in a theoretical and technical overview of the field. General understanding of all layers of the networking stack is required. However, the focus is mainly on networking, i.e. how to make networks work and how to keep them working. Thus, routing, switching and services that support networking (e.g. DHCP and DNS) are core topics. Furthermore, the course focuses on large-scale scenarios where networking can be challenging. The course is organised around weekly practical lab sessions and lectures that complement each other. The lectures give the theoretical background while the lab sessions give the necessary hands-on experience in putting theory into practice.

No formal requirements over and above the admission requirements.

This course has a limited number of spaces. A maximum of 22 students will be admitted on a "first come first serve" basis.

The course will provide the students with an understanding of what a mathematical model is and how we use models to gain insights into systems and processes in science and engineering. The course will train the students in using analytical and computational methods for analyzing and solving differential equations and prepare them for developing, analyzing and simulating mathematical models in their own projects. The models and methods taught in this course are generic and applicable not only in science, but also in various industrial contexts.

No formal requirements over and above the admission requirements.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of the course the student:

• knows the relevance of a selection of mathematical models to real-world phenomena
• has a thorough understanding of how mathematical modelling and scientific computing are utilized in various industrialized settings
• has a repertoire of methods to solve and/or analyze ordinary and partial differential equations (ODEs and PDEs)
• knows how to analyze the dynamics of an ODE system
• has a thorough understanding of the definitions of a smooth manifold and the tangent space
• knows the definitions and algebra of tensors and differential forms on a smooth manifold

Skills

On successful completion of this course the student:

• is able to derive mathematical models from facts and first principles for a selection of dynamical systems
• can apply mathematical modelling techniques on scenarios relevant to industry
• can implement mathematical models within the context of applied computer and information technology
• is able to analyse ODE systems and use bifurcation theory to elucidate the qualitative behavior of the systems
• is able to implement and use a selection of numerical methods for solving ODEs and PDEs
• is able to give examples of smooth manifolds and prove their smooth manifold property from the definition
• is able to use the geometric concepts and tools associated with smooth manifolds in the analysis of mathematical problems within mathematics, physics and engineering

General competence

On successful completion of this course the student:

• is aware of the usefulness and limitations of mathematical modelling as well as of pitfalls frequently encountered in modelling and simulation
• is able to discuss properties of a system using the equations of the mathematical model
• can explain and use numerical methods and interpret results of numerical simulations
• is aware of the role of smooth manifolds as one of the most fundamental concepts in mathematics and physics

The course is organized as a series of lectures and seminars where the subject material is presented and discussed. Between these sessions the students should work with problem solving, implementation of numerical methods and model simulations. The last part of the semester students will work with a compulsory individual project supervised by the course lecturer. The project will involve studies and analyses of a mathematical model and a rather extensive implementation of the numerical solution of the model. This will result in a report that should be 2000 - 4000 words of length plus figures.

None

The student can bring his/her own project report. The student is also allowed to make use of his/her own computer for the presentation.

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail.

Two internal examiners will assess the individual report and the oral presentation. External examiner is used periodically.