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Introduction to numerical analysis

Introduction to numerical analysis

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9.4/10 (Our Score)
Product is rated as #4 in category Artificial Intelligence

Numerical computations historically play a crucial role in natural sciences and engineering. These days however, it’s not only traditional «hard sciences»: whether you do digital humanities or biotechnology, whether you design novel materials or build artificial intelligence systems, virtually any quantitative work involves some amount of numerical computing . These days, you hardly ever implement the whole computation yourselves from scratch. We rely on libraries which package tried–and–tested, battle–hardened numerical primitives. It is vanishingly rare however that a library contains a single pre–packaged routine which does all what you need. Numerical computing involves assembling these building blocks into computational pipelines. This kind of work requires a general understanding of basic numerical methods, their strengths and weaknesses, their limitations and their failure modes. And this is exactly what this course is about. It is meant to be an introductory, foundational course in numerical analysis, with the focus on basic ideas. We will review and develop basic characteristics of numerical algorithms (convergence, approximation, stability, computational complexity and so on), and will illustrate them with several classic problems in numerical mathematics. You will also work on implementing abstract mathematical constructions into working prototypes of numerical code. Upon completion of this course, you will have an …

Instructor Details

Evgeni did his undergraduate studies in applied physics and mathematics in MIPT in Moscow, and a PhD in physics at the University of Massachusetts in Amherst. After finishing grad school, he did teaching and research in Germany, France and the U.K., and currently is an assistant professor in the School of Applied Mathematics at HSE. At HSE, Evgeni divides his time between teaching numerical analysis, doing computational physics, and developing open-source software in the Scientific Python ecosystem.

Specification: Introduction to numerical analysis

Duration

16 hours

Year

2019

Level

Intermediate

Certificate

Yes

Quizzes

Yes

6 reviews for Introduction to numerical analysis

4.5 out of 5
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  1. Avatar

    Dawars

    Great course with useful homework assignments in Jupyter notebook. Highly recommended!

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  2. Avatar

    Pingchuan M

    Very nice overall illustration of all relevant topics in numerical analysis. Laid a solid foundation if you want to dive deeper into any specific domain.

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    Mahadev D

    nice

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    Sunny J

    Awesome Course

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  5. Avatar

    Chintan S

    The course hardly provides any examples of the numerical methods discussed. If you are new to Numerical Methods, it would be better to learn Numerical Methods elsewhere and use this course only to build Python functions on your own in the assignments. These programming assignments are also not very crisp and you spend a lot of time figuring out how to implement. The only great takeaway from this course for me personally was the handling of catastrophic cancellation problems.

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    Victor A M G

    Excelent course. Really liked how the teacher explained the course in general. I would upgrade it with more examples reviewed.

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