Stanford University

Description Machine Learning is the basis for the most exciting careers in data analysis today. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies. Major perspectives covered include: probabilistic versus non-probabilistic…

Description Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are…

Description Eating patterns that begin in childhood affect health and well-being across the lifespan. The culture of eating has changed significantly in recent decades, especially in parts of the world where processed foods dominate our dietary intake. This course examines contemporary child nutrition and the impact of the individual decisions made by each family. The…

Description The objectives of this course are: -To introduce participants to different concepts of love, to empower them to be conscious of the power of love and the possibility of practicing it in everyday life, and to highlight in particular the idea of love as a force for social justice. -To communicate a sense of…

Description Popularized by movies such as “A Beautiful Mind”, game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Over four weeks of lectures, this advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective…

Description This course focuses on women’s health and human rights issues from infancy through old age, including information about positive interventions relating to those issues. Learners are encouraged to interact with each other through interactive discussions. It is important to us that this course be available to all learners. We encourage you to apply for…

Description The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search). Price: Enroll For Free! View Class Language: English Subtitles: English Shortest Paths Revisited, NP-Complete Problems and What…

Description Stanford’s Short Course on Breastfeeding was designed for new mothers and the people who support them. This engaging, one-week learning experience, provides participants with everything they need to know to more successfully establish breastfeeding – or support a new mother who has decided to breastfeed. We created the course because we recognize that there…