Review the basics of discrete math and probability before enhancing your probability skills and learning how to interpret data with tools such as the central limit theorem, confidence intervals and more. Complete short weekly mathematical assignments.
Statistics for Data Science Essentials
Statistics for Data Science Essentials
包含在 
中
您将学到什么
Comprehensively review probability and understand its role as a building block of data science.
Apply the central limit theorem, confidence intervals and the method of maximum likelihood to solving data science problems.
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作业
16 项作业
授课语言：英语（English）
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积累特定领域的专业知识
本课程是 AI and Machine Learning Essentials with Python 专项课程 专项课程的一部分
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该课程共有4个模块
In the first week of the course, we’ll introduce you to a broad definition of data science and go over some of its main building blocks. To prepare, we'll spend some time reviewing discrete math fundamentals. By the end of the week, we will solve our first data science task using random sampling.
涵盖的内容
8个视频1篇阅读材料4个作业
The second week of our course is devoted to probability: since probability is the main language used by almost every data science concept, we will commit some time to deepening our understanding of it. By the end of the week, you will have far more tools in your probability toolkit, which will serve you throughout your AI and machine learning journey.
涵盖的内容
6个视频4个作业
In this week, we will build up our general framework of statistical estimation, taking from several of the concepts we have discussed and more that we will continue to add this week. We will start by going over the sample mean, and we will analyze how good this is as an estimator. We will then explore the Central Limit Theorem, one of the most effective and widely-used tools in statistics and data science. We will also continue some probability review.
涵盖的内容
8个视频4个作业
Now that we have learned the important machinery of the Central Limit Theorem, we are ready to learn about confidence intervals this week. Confidence intervals are the main quantities to characterize error bars in almost any area of data science and machine learning. After going through confidence intervals and some examples, we will also explore a more general perspective on estimation: point estimation.
涵盖的内容
7个视频1篇阅读材料4个作业
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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.
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