Informações sobre o curso

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Certificados compartilháveis
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100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário

All the themes demand only mathematical background amongst the ordinary school program and initial Python programming skills.

Aprox. 31 horas para completar
Inglês
Legendas: Inglês
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário

All the themes demand only mathematical background amongst the ordinary school program and initial Python programming skills.

Aprox. 31 horas para completar
Inglês
Legendas: Inglês

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National Research University Higher School of Economics

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Este curso é parte da graduação 100% on-line Master of Data Science da National Research University Higher School of Economics. Caso seja aceito para o programa completo, seus cursos contarão para sua graduação.

Programa - O que você aprenderá com este curso

Semana
1

Semana 1

5 horas para concluir

Introduction: Numerical Sets, Functions, Limits

5 horas para concluir
14 vídeos (Total 103 mín.), 4 leituras, 3 testes
14 videos
Welcome to the Course!2min
Introduction to the Week1min
Numerical Sets13min
Mappings and Quantifiers3min
Functions : Definitions10min
Functions: Arithmetic and Composition8min
Graph Transformations11min
Limit of Sequences7min
Limit of Sequences: Examples11min
Limit of Sequences: Arithmetic Rules12min
Limits of Sequences: Definition of e7min
The Indeterminate Forms3min
Comparison between Polynomial, Exponential and Logarithmic Functions10min
4 leituras
About the University10min
Real numbers10min
Newton's Binomial Theorem10min
The Definition of e30min
3 exercícios práticos
Practice Quiz #115min
Practice Quiz #215min
First Week Final Test1h
Semana
2

Semana 2

5 horas para concluir

Limits and Multivariate Functions

5 horas para concluir
13 vídeos (Total 110 mín.)
13 videos
From Sequences to Functions3min
Function’s Limit6min
Function’s Limit: Examples9min
Function’s Limit: Arithmetic8min
Function’s Limit: Indeterminate Forms and Boundary Rule10min
Two Important Limits10min
Asymptotic Notations6min
Big-O7min
Little-o11min
Multivariate Functions: Definitions13min
Multivariate Functions: Limits8min
Multivariate limits: Examples12min
3 exercícios práticos
Practice Quiz #130min
Practice Quiz #230min
Second Week Final Test2h
Semana
3

Semana 3

5 horas para concluir

Derivatives and Linear Approximations: Singlevariate Functions

5 horas para concluir
13 vídeos (Total 74 mín.), 3 leituras, 4 testes
13 videos
Derivative: Definition3min
Differentiability3min
Derivatives: Examples8min
Arithmetic of Derivatives7min
Derivatives: Chain Rule8min
Tangent Line: Equation6min
Linear Approximations9min
Mean Value Theorem4min
Second Derivatives6min
Convexity3min
Extrema and First Derivative6min
Extrema and Second Derivative3min
3 leituras
Derivatives: Logarithmic Rule10min
Derivatives: Inverse Functions10min
Extrema: Clearing the Air10min
4 exercícios práticos
Practice Quiz #130min
Practice Quiz #230min
Practice Quiz #330min
Third Week Final Test1h
Semana
4

Semana 4

4 horas para concluir

Derivatives and Linear Approximations: Multivariate Functions

4 horas para concluir
14 vídeos (Total 96 mín.)
14 videos
Tangent Plane: Motivation1min
Partial Derivatives: Definition3min
Partial Derivatives: Examples5min
Tangent Plane: Definition8min
Differentiability of Multivariate Function3min
Differentiability of Multivariate Function: Example9min
Differentiability: Sufficient Condition4min
Basic Geometry and Gradient11min
Chain Rule: One Independent Variable7min
Second Partial Derivatives9min
Differentials of Multivariate Functions13min
Convexity4min
Second Partial Derivatives: Convexity11min
3 exercícios práticos
Practice Quiz #130min
Practice Quiz #230min
Forth Week Final Test1h

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Sobre Programa de cursos integrados Mathematics for Data Science

Behind numerous standard models and constructions in Data Science there is mathematics that makes things work. It is important to understand it to be successful in Data Science. In this specialisation we will cover wide range of mathematical tools and see how they arise in Data Science. We will cover such crucial fields as Discrete Mathematics, Calculus, Linear Algebra and Probability. To make your experience more practical we accompany mathematics with examples and problems arising in Data Science and show how to solve them in Python....
Mathematics for Data Science

Perguntas Frequentes – FAQ

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

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    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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