- Bayesian Statistics
- Machine Learning
- Mathematics
- Probability
- Linear Regression
- Linear Equation
- Eigenvalues And Eigenvectors
- Linear Algebra
- Determinants
- Calculus
- Mathematical Optimization
- Gradient Descent

# Mathematics for Machine Learning and Data Science 专项课程

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

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## 您将学到的内容有

A deep understanding of the math that makes machine learning algorithms work.

Statistical techniques that empower you to get more out of your data analysis.

Fundamental skills that employers desire, helping you ace machine learning interview questions and land your dream job.

Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence

## 您将获得的技能

## 关于此 专项课程

## 应用的学习项目

By the end of this Specialization, you will be ready to:

Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence

Apply common vector and matrix algebra operations like dot product, inverse, and determinants

Express certain types of matrix operations as linear transformations

Apply concepts of eigenvalues and eigenvectors to machine learning problems

Optimize different types of functions commonly used in machine learning

Perform gradient descent in neural networks with different activation and cost functions

Describe and quantify the uncertainty inherent in predictions made by machine learning models

Understand the properties of commonly used probability distributions in machine learning and data science

Apply common statistical methods like MLE and MAP

Assess the performance of machine learning models using interval estimates and margin of errors

Apply concepts of statistical hypothesis testing

对员工进行热门技能培训能否为您的公司带来益处？

体验 Coursera 企业版对员工进行热门技能培训能否为您的公司带来益处？

体验 Coursera 企业版## 专项课程的运作方式

### 加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习，请直接注册专项课程，或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时，您将自动订阅整个专项课程。您可以只完成一门课程，您可以随时暂停学习或结束订阅。访问您的学生面板，跟踪您的课程注册情况和进度。

### 实践项目

每个专项课程都包括实践项目。您需要成功完成这个（些）项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程，则需要在开始之前完成其他所有课程。

### 获得证书

在结束每门课程并完成实践项目之后，您会获得一个证书，您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

## 常见问题

What is the refund policy?

Can I just enroll in a single course?

Is financial aid available?

Can I take the course for free?

Is this course really 100% online? Do I need to attend any classes in person?

I’m not good at math, is this course still for me?

What areas of mathematics will I learn in this course?

Why is mathematics for machine learning and data science important?

How long does it take to complete the Specialization?

What background knowledge is necessary?

Do I need to take the courses in a specific order?

Will I earn university credit for completing the Specialization?

What will I be able to do after completing Mathematics for Machine Learning and Data Science?

Is this a standalone course or a specialization?

Do I need to take the courses in a specific order?

Can I apply for financial aid?

How much does the specialization cost?

Can I apply for financial aid?

Can I audit the specialization?

Will I receive a certificate at the end of the specialization?

I want to purchase this specialization for my employees. How can I do that?

How do I get a receipt to get this reimbursed by my employer?

Are all courses of this specialization ready for enrollment?

还有其他问题吗？请访问 学生帮助中心。