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Curriculum for both tracks are outlined below: Build expertise and career skills in the most important computer science topics.Courses and projects cover subjects like: Learn parallel programming and how to achieve peak performance from multi-core CPU and many-core GPU architectures.Discover the fundamentals of numerical analysis, and how it’s applied to scientific and engineering simulations, with applications ranging from creating video game worlds to virtual medicine.
You’ll also learn to retrieve information from unstructured data sources, such as natural language text.
Coursework on the cloud computing technology, infrastructure and application development that is essential for supporting the discovery and extraction of knowledge from big data.
Learn to manage a large software project from specification through implementation, testing, and maintenance.
You‘ll also learn to manage large enterprise-level codebases.
It is focused around the use of finite differences to solve differential equations.
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After an introduction to the concept of numerical solutions to the mathematical equations, the course will detail the concept of finite differences to solve initial value problems, boundary value problems and the heat equation.
After the basic are covered, a series of applications will be presented covering a range of applied geophysical problems.
The module covers: This aim of the module is to introduce standard computational methods to solve mathematical and geophysical problems such as heat diffusion, wave propagation and stress equilibrium.
Master languages, compilers, and libraries that are suited for various parallel applications and platforms.
Build your knowledge of the fundamental statistical models and numerical optimizations of machine learning, including deep learning, with applications in computer vision, natural language processing and intelligent user interaction.