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.
oferecido por
Data Science Math Skills
Universidade DukeInformações sobre o curso
166.677 visualizações recentes
Resultados de carreira do aprendiz
12%
consegui um benefício significativo de carreira com este curso
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível iniciante
Aprox. 13 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
Habilidades que você terá
- Bayes' Theorem
- Bayesian Probability
- Probability
- Probability Theory
Resultados de carreira do aprendiz
12%
consegui um benefício significativo de carreira com este curso
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível iniciante
Aprox. 13 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade Duke
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.
Programa - O que você aprenderá com este curso
18 minutos para concluir
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 minutos para concluir
1 vídeo (Total 3 mín.), 2 leituras
4 horas para concluir
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 horas para concluir
10 vídeos (Total 93 mín.), 4 leituras, 4 testes
3 horas para concluir
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 horas para concluir
8 vídeos (Total 72 mín.), 3 leituras, 3 testes
3 horas para concluir
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 horas para concluir
7 vídeos (Total 66 mín.), 3 leituras, 3 testes
3 horas para concluir
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 horas para concluir
8 vídeos (Total 66 mín.), 4 leituras, 4 testes
Avaliações
- 5 stars63,88%
- 4 stars28,02%
- 3 stars5,72%
- 2 stars1,54%
- 1 star0,82%
Principais avaliações do DATA SCIENCE MATH SKILLS
por PP26 de fev de 2018
The content of the course as a whole is interesting as a good synthesis of basic skills, even though the content of the weeks 3 and 4 lacks of clarity compared to the content of the weeks 1 and 2.
por KC20 de out de 2020
Weeks 1-3 were quality. Week 4 was a little sloppy in the instructional videos and less clear than in Weeks 1-3. Overall, concise refresher of various mathematical subjects useful to data science.
por MG27 de mar de 2018
Please include integration, algorithm analysis (big O, theta, omega), recursion and induction. Your course is helpful, thank you. If you add those things I've mentioned it would be absolute gold.
por NE3 de jan de 2021
I want to thank my educators for this wonderful job that they are doing.i have learn so much from you guys and i want to thank you all for your kind support in this data science maths skills.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
O que recebo ao adquirir o Certificado?
Existe algum auxílio financeiro disponível?
Will I receive a transcript from Duke University for completing this course?
Mais dúvidas? Visite o Central de Ajuda ao estudante.
