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Learn the essential ideas of Computer Science, this course demystifies and brings those patterns to life, which is useful for anyone using computers today.
Free online courses from Stanford University. Stanford Online is Stanford’s online learning portal, offering learners around the world access to Stanford’s extended education, professional development, and lifelong learning opportunities.
Jan 4, 2011 · Course Overview: Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic analysis; divide-and-conquer algorithms and recurrences; greedy algorithms; data structures; dynamic programming; graph algorithms; and randomized algorithms. Required textbook: Kleinberg and Tardos, Algorithm Design, 2005.
What You Need to Get Started. Basic familiarity with computers and productivity software. No calculus required. By the end of this course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts.
Accounting for Managers and Entrepreneurs. MS&E240. Stanford School of Engineering. Summer 2023-24: Online, instructor-led - Enrollment Open. Course.
Introduction to applied machine learning. In this course, you'll learn about machine learning techniques such as linear regression, logistic regression, naive Bayes, SVMs, clustering, and more. In addition, you'll also learn the practical, hands-on, skills and techniques needed to get learning techniques to work well in practice.
Free Online Courses. Browse our collection of free online courses taught by Stanford instructors and industry experts. Free Content Library. Explore on-demand webinars, articles, eBooks, and more on a variety of topics.
