4.5
estrellas
10,927 calificaciones

96 %

Daniel Egger +1 instructores más

348.873 ya inscrito

Ofrecido Por

Data Science Math Skills

Universidad Duke

Acerca de este Curso

208.417 vistas recientes

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. 
Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material.

Topics include:
~Set theory, including Venn diagrams
~Properties of the real number line
~Interval notation and algebra with inequalities
~Uses for summation and Sigma notation
~Math on the Cartesian (x,y) plane, slope and distance formulas
~Graphing and describing functions and their inverses on the x-y plane,
~The concept of instantaneous rate of change and tangent lines to a curve
~Exponents, logarithms, and the natural log function.
~Probability theory, including Bayes’ theorem.

While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization.  Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." 

Good luck and we hope you enjoy the course!

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Nivel principiante

Aprox. 13 horas para completar

Inglés (English)

¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?

Prueba Coursera para negocios

Habilidades que obtendrás

Bayes' Theorem
Bayesian Probability
Probability
Probability Theory

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Nivel principiante

Aprox. 13 horas para completar

Inglés (English)

¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?

Prueba Coursera para negocios

Instructores

Calificación del instructor

4,46/5 (3078 calificaciones)

Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling

Pratt School of Engineering, Duke University

1.001.715 alumnos

8 cursos

Paul Bendich

Assistant research professor of Mathematics; Associate Director for Curricular Engagement at the Information Initiative at Duke

Mathematics

348.973 alumnos

2 cursos

Ofrecido por

Universidad Duke

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Programa - Qué aprenderás en este curso

Calificación del contenido96%(45,206 calificaciones)

Semana

Semana 1

18 minutos para completar

Welcome to Data Science Math Skills

18 minutos para completar

1 video (Total 3 minutos), 2 lecturas

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 - Basics and Vocabulary9m

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

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

Semana

Semana 2

3 horas para completar

Functions and Graphs

3 horas para completar

8 videos (Total 72 minutos), 3 lecturas, 3 cuestionarios

8 videos

Cartesian Plane - Plotting Points7m

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

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

Semana

Semana 3

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 - Slope of a Graph at a Point10m

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

Semana

Semana 4

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

Probability Definitions and Notation7m

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

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

4.5

2441 reseña

5 stars
63,79 %
4 stars
28,01 %
3 stars
5,77 %
2 stars
1,60 %
1 star
0,81 %

Principales reseñas sobre DATA SCIENCE MATH SKILLS

por WH11 de ago. de 2020

For the part of Bayes' theorem, I think the explanation is no clear or through enough. Maybe more break-down is necessary. And the other parts are really good. I really enjoy taking this course.

por SP29 de may. de 2020

Great refresher and primer. The section on Probability and Bayes Theory needs a lot more support material (video and notes) as it can get tricky and abstract, especially when doing the quizzes.

por DN17 de nov. de 2019

I thought this course was a nice refresher on basic mathematical concepts and it introduced me to set theory and probability very well! I think I am better prepared for data science afterward!

por PP26 de feb. 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.

Ver todas las reseñas

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.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.
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.

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Data Science Math Skills

Data Science Math Skills

Acerca de este Curso

Habilidades que obtendrás