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.
Data Science Math Skills
ofrecido por
Data Science Math Skills
Universidad Duke
Acerca de este Curso
217,814 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
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
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. 16 horas para completar
Sugerido: Four weeks, 3-5 hours per week.
Inglés (English)
Subtítulos: Inglés (English)
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
Revisiones
Principales revisiones sobre DATA SCIENCE MATH SKILLS
por ASJan 11, 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 PSJul 22, 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.
por PPFeb 26, 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 MGMar 27, 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 DNNov 17, 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 JVDec 10, 2019
First 3 weeks were easy going and the last week was a bit more challenging. I think more examples could be included in the lectures to understand Bayes' Theorem at the most fundamental level.
por HHAug 2, 2017
Loved it! Started off easy but got a little tricky in the end with Bayes Theorem. Glad I know which data / math areas I need to brush up on for my job. Thanks, Duke University and Coursera!
por PMSep 16, 2017
Good refresher. Weeks 3 and 4 are much more difficult to follow than one and two. Part of this is due to the subject matter but also a change of teacher / and style makes it more difficult.
por GPMar 6, 2018
Looking forward to advanced courses on Linear algebra, eculidean geometry that would make the concepts of vectors, matrices, plane and any application of those in the data science problems.
por KKJul 14, 2019
sometime the lecture is too easy to understand and after some week it goes too hard to understand even it not a hard thing but sometime the lecturer make it so hard so it can make confuse.
por APFeb 7, 2018
A great review of A level statistics which I had long since forgotten but suddenly found myself needing again. A really good balance of work through the weeks and at just the right level.
por AROct 13, 2019
The course was very good and well thought of, a great refresher for very important concepts, the instructors are very good at simplifying the material and making it very understandable.
Acerca de 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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿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.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
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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