Для кого этот курс: This course is for anyone who has basic math skills, but is interested in learning or relearning algebra or pre-calculus so they can be successful in other data science math courses.


Автор:   Университет Дьюка

  • Daniel Egger

    Преподаватели:    Daniel Egger, Executive in Residence and Director, Center for Quantitative Modeling

    Pratt School of Engineering, Duke University

  • Paul Bendich

    Преподаватели:    Paul Bendich, Assistant research professor of Mathematics; Associate Director for Curricular Engagement at the Information Initiative at Duke

    Mathematics
УровеньBeginner
ВыполнениеFour weeks, 3-5 hours per week.
Язык
English
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Авторы
Университет Дьюка
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
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Оценка 4.4 из 5 по 167 отзывам

Instructors made this subject so much easier for me to learn!

Awesome Course!

A tremendously useful primer on the fundamentals of data science math. This course is a particularly good option for individuals who have seen some amount of calculus and algebra but haven't used those methods in a long while and need to review. Thorough, easy-to-understand material.

I would suggest to the course facilitators that they develop the provided lecture notes -- already a useful tool -- into a full-fledged text. I'm not suggesting something much longer than what they already have, but simply taking that document and adding a bit more rich content. While the notes are useful for more carefully studying the math being done in the lectures, even a bit of effort putting some pedagogy into the notes and combining them into a single document (which I did for the sake of printing) would create a hugely valuable resource.

I love this Course!!!!