Machine Learning - Stanford University



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The following course, offered by Coursera, will help you improve your skills and achieve your professional goals. During the program you will study different subjects which are deemed to be useful for those who want to enhance their professional career. Sign up for more information!

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Course programme

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas. Can I earn a Course Certificate if I completed this course before they were available? In order to verify one’s identity and maintain academic integrity, learners who completed assignments or quizzes for Machine Learning prior to November 1st will need to redo and resubmit these assessments in order to earn a Course Certificate. To clarify, both quizzes and programming assignments need to be resubmitted. Though your deadlines may have technically passed, please be assured that you may resubmit both types of assessments at any time. We apologize for the inconvenience and appreciate your patience as we strive to ensure the integrity and value of our certificates. Please note that, in order to earn a Course Certificate, you must complete the course within 180 days of payment, or by May 1, 2016, whichever is earlier.Online learning plays a key role in lifelong learning. In fact, a recent report by the United States Department of Education found that "the courses that include online education (either completely virtual or blended learning) produce, on average, much stronger learning outcomes for students courses They are conducted exclusively in person. Based on an approach developed by educational psychologist Benjamin Bloom, the mastery learning helps students to fully understand a subject before moving on to a more advanced. In Coursera, usually we give an answer immediately to the concepts that the student does not understand feedback. In many cases, we offer random versions of assessments for the student to return to school and retrying until mastered the concept.