Exploration of Data Science requires certain background in probability and statistics. This course introduces you to the necessary sections of probability theory and statistics, guiding you from the very basics all way up to the level required for jump starting your ascent in Data Science.
About this Course
National Research University Higher School of Economics
National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more.
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TOP REVIEWS FROM PROBABILITY THEORY, STATISTICS AND EXPLORATORY DATA ANALYSIS
Very nice approach to such a vast topic , making it more understandable. Such type of interactive lectures are advisable for courses on Calculus and Algebra from the same University.
Ilya Schurov explains concepts very well, and this course is a great start to begin the journey into data science. Also, the inclusion of some programming is appreciated!
Excellent course. To the point with no fluff. The professor explained everything in just the right amount of detail and the inclusion of python is great too.
One of the best courses for Probability and statistics, the course structure and syllabus was really very organized. I enjoyed completing this course.
About the Mathematics for Data Science Specialization
Behind numerous standard models and constructions in Data Science there is mathematics that makes things work. It is important to understand it to be successful in Data Science. In this specialisation we will cover wide range of mathematical tools and see how they arise in Data Science. We will cover such crucial fields as Discrete Mathematics, Calculus, Linear Algebra and Probability. To make your experience more practical we accompany mathematics with examples and problems arising in Data Science and show how to solve them in Python.
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