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Старый 02.03.2013, 17:06   #25
Uzanka
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Регистрация: 16.04.2012
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записалась на июнь. Курс будет читаться впервые, т.е. возможны недоработки в плане тестов (первый раз идет "обкатка" курса)

Coding the Matrix: Linear Algebra through Computer Science Applications
Philip Klein
Learn the concepts and methods of linear algebra, and how to use them to think about computational problems arising in computer science. Coursework includes building on the concepts to write small programs and run them on real data.

Next Session:
June 2013 (8 weeks long)
Workload: 7-10 hours/week
https://www.coursera.org/#course/matrix

more

About the Course

When you take a digital photo with your phone or transform the image in Photoshop, when you play a video game or watch a movie with digital effects, when you do a web search or make a phone call, you are using technologies that build upon linear algebra. Linear algebra provides concepts that are crucial to many areas of computer science, including graphics, image processing, cryptography, machine learning, computer vision, optimization, graph algorithms, quantum computation, computational biology, information retrieval and web search. Linear algebra in turn is built on two basic elements, the matrix and the vector.

In this class, you will learn the concepts and methods of linear algebra, and how to use them to think about problems arising in computer science. You will write small programs in the programming language Python to implement basic matrix and vector functionality and algorithms, and use these to process real-world data to achieve such tasks as: two-dimensional graphics transformations, face morphing, face detection, image transformations such as blurring and edge detection, image perspective removal, audio and image compression, searching within an image or an audio clip, classification of tumors as malignant or benign, integer factorization, error-correcting codes, secret-sharing, network layout, document classification, and computing Pagerank (Google's ranking method).

Recommended Background

You are not expected to have any background in linear algebra. You need not know Python, but you should have at least some exposure to programming. You should also be prepared to read and write a few simple mathematical proofs.

Suggested Readings

We will link to an optional textbook (currently in the works) that covers essentially the same material as the course but in greater depth and with more examples and some additional topics.

FAQ

•Will I get a statement of accomplishment after completing this class?
Yes. Students who successfully complete the class will receive a statement of accomplishment signed by the instructor.
•What resources will I need for this class?
You will need a computer with Python installed (version 3.x). We will provide additional Python modules for you to download.
•What is the coolest thing I'll learn if I take this class?
Here are some cool things: removing the perspective from an image, how Google's Pagerank works, error-correcting codes, image compression, a simple machine-learning algorithm applied to cancer data.


Добавлено через 7 минут
Скачала также вспомогательный материал для Model Thinking - карты разума и описание всех моделей по ссылке молодого человека, которую дала выше. Очень подробное описание моделей. Представляю сколько он потратил времени на это всё. Очень серьезный подход.. и тщательный. У меня никогда не хватает сил на подобное

Скачала также программу для карт разума (в которой он строит). Вроде всё работает. Сама еще не пробовала в ней строить. Пока смотрела уже готовые карты для этого курса.

здесь еще есть немного отзывов о курсах, которые мы на форуме проходили. У нас есть девушки-химики. Может быть кому-то будут интересны и эти курсы.
Uzanka вне форума   Ответить с цитированием
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