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.
ofrecido por
Data Science Math Skills
Universidad DukeAcerca de este Curso
622,075 vistas recientes
Resultados profesionales del estudiante
41%
comenzó una nueva carrera después de completar estos cursos
34%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (de Brasil), Ruso (Russian), Inglés (English), Español (Spanish)
Habilidades que obtendrás
Bayes' TheoremBayesian ProbabilityProbabilityProbability Theory
Resultados profesionales del estudiante
41%
comenzó una nueva carrera después de completar estos cursos
34%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (de Brasil), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad 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 - Qué aprenderás en este curso
18 minutos para completar
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 completar
1 video (Total 3 minutos), 2 lecturas
1 video
2 lecturas
Course Information5m
Weekly feedback surveys10m
4 horas para completar
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 completar
10 videos (Total 93 minutos), 4 lecturas, 4 cuestionarios
10 videos
Sets - Medical Testing Example11m
Sets - Venn Diagrams7m
Numbers - The Real Number Line9m
Numbers - Less-than and Greater-than6m
Numbers - Algebra With Inequalities10m
Numbers - Intervals and Interval Notation7m
Sigma Notation - Introduction to Summation9m
Sigma Notation - Simplification Rules7m
Sigma Notation - Mean and Variance12m
4 lecturas
A note about the video lectures in this lesson3m
A note about the video lectures in this lesson10m
A note about the video lectures in this lesson10m
Feedback10m
4 ejercicios de práctica
Practice quiz on Sets15m
Practice quiz on the Number Line, including Inequalities25m
Practice quiz on Simplification Rules and Sigma Notation20m
Graded quiz on Sets, Number Line, Inequalities, Simplification, and Sigma Notation35m
3 horas para completar
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 completar
8 videos (Total 72 minutos), 3 lecturas, 3 cuestionarios
8 videos
Cartesian Plane - Distance Formula10m
Cartesian Plane - Point-Slope Formula for Lines8m
Cartesian Plane: Slope-Intercept Formula for Lines7m
Functions - Mapping from Sets to Sets7m
Functions - Graphing in the Cartesian Plane11m
Functions - Increasing and Decreasing Functions10m
Functions - Composition and Inverse10m
3 lecturas
A note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
Feedback10m
3 ejercicios de práctica
Practice quiz on the Cartesian Plane15m
Practice quiz on Types of Functions20m
Graded quiz on Cartesian Plane and Types of Function40m
3 horas para completar
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 completar
7 videos (Total 66 minutos), 3 lecturas, 3 cuestionarios
7 videos
Tangent Lines - The Derivative Function9m
Using Integer Exponents7m
Simplification Rules for Algebra using Exponents11m
How Logarithms and Exponents are Related12m
The Change of Base Formula4m
The Rate of Growth of Continuous Processes11m
3 lecturas
A note about the video lectures in this lesson10m
A note about the video lectures in this lesson3m
Feedback10m
3 ejercicios de práctica
Practice quiz onTangent Lines to Functions10m
Practice quiz on Exponents and Logarithms40m
Graded quiz on Tangent Lines to Functions, Exponents and Logarithms45m
3 horas para completar
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 completar
8 videos (Total 66 minutos), 4 lecturas, 4 cuestionarios
8 videos
Joint Probabilities6m
Permutations and Combinations12m
Using Factorial and “M choose N”6m
The Sum Rule, Conditional Probability, and the Product Rule8m
Bayes’ Theorem (Part 1)10m
Bayes’ Theorem (Part 2)5m
The Binomial Theorem and Bayes Theorem8m
4 lecturas
A note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
A note about the video lectures in this lesson3m
Feedback10m
4 ejercicios de práctica
Practice quiz on Probability Concepts25m
Practice quiz on Problem Solving25m
Practice quiz on Bayes Theorem and the Binomial Theorem25m
Probability (basic and Intermediate) Graded Quiz50m
Reseñas
Principales reseñas sobre DATA SCIENCE MATH SKILLS
por RS5 de may. de 2020
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!!
por AS11 de ene. de 2019
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)
por VC16 de may. de 2020
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)
por PS22 de jul. de 2017
This is neat little course to revise math fundamentals. I generally find learning probability a little tricky. This course helped me a lot in better understanding Bayes Theorem. Thank you professors.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
- es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
- Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si compro el Certificado?
Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.
Is financial aid available?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el vínculo de Ayuda económica que está debajo del botón 'Inscribirse' a la izquierda. Se te pedirá que completes una solicitud y recibirás una notificación cuando se apruebe. Obtén más información.
Will I receive a transcript from Duke University for completing this course?
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
¿Recibiré crédito universitario por completar el Curso?
Este Curso no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del curso para obtener crédito. Consulta con tu institución para obtener más información. Los Títulos en línea y los Certificados Mastertrack™ de Coursera brindan la oportunidad de obtener créditos universitarios.
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