## 關於此 專項課程

The purpose of this series of courses is to teach the basics of Computational Statistics for the purpose of performing inference to aspiring or new Data Scientists. This is not intended to be a comprehensive course that teaches the basics of statistics and probability nor does it cover Frequentist statistical techniques based on the Null Hypothesis Significance Testing (NHST). What it does cover is: The basics of Bayesian statistics and probability Understanding Bayesian inference and how it works The bare-minimum set of tools and a body of knowledge required to perform Bayesian inference in Python, i.e. the PyData stack of NumPy, Pandas, Scipy, Matplotlib, Seaborn and Plot.ly A scalable Python-based framework for performing Bayesian inference, i.e. PyMC3 With this goal in mind, the content is divided into the following three main sections (courses). Introduction to Bayesian Statistics - The attendees will start off by learning the the basics of probability, Bayesian modeling and inference in Course 1. Introduction to Monte Carlo Methods - This will be followed by a series of lectures on how to perform inference approximately when exact calculations are not viable in Course 2. PyMC3 for Bayesian Modeling and Inference - PyMC3 will be introduced along with its application to some real world scenarios. The lectures will be delivered through Jupyter notebooks and the attendees are expected to interact with the notebooks.

100% 在線課程

100% 在線課程

## 專項課程的運作方式

### 加入課程

Coursera 專項課程是幫助您掌握一門技能的一系列課程。若要開始學習，請直接註冊專項課程，或預覽專項課程並選擇您要首先開始學習的課程。當您訂閱專項課程的部分課程時，您將自動訂閱整個專項課程。您可以只完成一門課程，您可以隨時暫停學習或結束訂閱。訪問您的學生面板，跟踪您的課程註冊情況和進度。

### 獲得證書 3.3
21 個評分
11 條評論

3.0
10 個評分
2 條評論

## 提供方 