Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.
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Data Science Math Skills
Университет ДьюкаОб этом курсе
Недавно просмотрено: 223 984
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Сертификат, ссылками на который можно делиться с другими людьми
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100% онлайн
Начните сейчас и учитесь по собственному графику.
Начальный уровень
Прибл. 13 часов на выполнение
Английский
Субтитры: Арабский, Французский, Португальский (Европа), Итальянский, Вьетнамский, Немецкий, Русский, Английский, Испанский
Приобретаемые навыки
Bayes' TheoremBayesian ProbabilityProbabilityProbability Theory
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Начальный уровень
Прибл. 13 часов на выполнение
Английский
Субтитры: Арабский, Французский, Португальский (Европа), Итальянский, Вьетнамский, Немецкий, Русский, Английский, Испанский
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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.
Программа курса: что вы изучите
18 минут на завершение
Welcome to Data Science Math Skills
This short module includes an overview of the course's structure, working process, and information about course certificates, quizzes, video lectures, and other important course details. Make sure to read it right away and refer back to it whenever needed
18 минут на завершение
1 видео ((всего 3 мин.)), 2 материалов для самостоятельного изучения
4 ч. на завершение
Building Blocks for Problem Solving
This module contains three lessons that are build to basic math vocabulary. The first lesson, "Sets and What They’re Good For," walks you through the basic notions of set theory, including unions, intersections, and cardinality. It also gives a real-world application to medical testing. The second lesson, "The Infinite World of Real Numbers," explains notation we use to discuss intervals on the real number line. The module concludes with the third lesson, "That Jagged S Symbol," where you will learn how to compactly express a long series of additions and use this skill to define statistical quantities like mean and variance.
4 ч. на завершение
10 видео ((всего 93 мин.)), 4 материалов для самостоятельного изучения, 4 тестов
3 ч. на завершение
Functions and Graphs
This module builds vocabulary for graphing functions in the plane. In the first lesson, "Descartes Was Really Smart," you will get to know the Cartesian Plane, measure distance in it, and find the equations of lines. The second lesson introduces the idea of a function as an input-output machine, shows you how to graph functions in the Cartesian Plane, and goes over important vocabulary.
3 ч. на завершение
8 видео ((всего 72 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
3 ч. на завершение
Measuring Rates of Change
This module begins a very gentle introduction to the calculus concept of the derivative. The first lesson, "This is About the Derivative Stuff," will give basic definitions, work a few examples, and show you how to apply these concepts to the real-world problem of optimization. We then turn to exponents and logarithms, and explain the rules and notation for these math tools. Finally we learn about the rate of change of continuous growth, and the special constant known as “e” that captures this concept in a single number—near 2.718.
3 ч. на завершение
7 видео ((всего 66 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
3 ч. на завершение
Introduction to Probability Theory
This module introduces the vocabulary and notation of probability theory – mathematics for the study of outcomes that are uncertain but have predictable rates of occurrence.
3 ч. на завершение
8 видео ((всего 66 мин.)), 4 материалов для самостоятельного изучения, 4 тестов
Рецензии
Лучшие отзывы о курсе DATA SCIENCE MATH SKILLS
от партнера VS22 сент. 2020 г.
This course syllabus is great. It starts wonderfully. Week 1 to 4 is taught by Paul Bendich, and Daniel Egger the instruction is awesome. Effective way to refresh and add the Data Science math skills!
от партнера VC16 мая 2020 г.
Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)
от партнера AS11 янв. 2019 г.
Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)
от партнера RS5 мая 2020 г.
This was mostly review for me though probability especially Beyes Theorem derivation was new. The instructors provided clear often refreshing ways to look at material. Thank you for a great class!!
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Что я получу, оплатив сертификацию?
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Will I receive a transcript from Duke University for completing this course?
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