Background

The Distributed Statistical Computing course was developed and taught by Dr. Feng Li in 2014 for a joint master’s program in statistics with prestigious universities, Peking University, Renmin University of China, Central University of Finance and Economics, University of Chinese Academy of Sciences, and Capital University of Economics and Business.

This course is also offered by Dr. Feng Li for the Business Analytics program at Peking University since 2020.

Prerequisites

• Basic knowledge of statistics
• Basic knowledge in computing

Literature

• Distributed statistical computing [New online book | Print version]
• Lecture notes
• Demo Hadoop/Spark configurations
• Basic Hadoop/Spark Tutorial for Statisticians

Teaching Videos

• The Chinese version of teaching videos are also available on https://space.bilibili.com/509963672

Slides and lecture notes

Read with online Jupyter Notebook viewer

• Download all Jupyter Notebooks in a zip file.
• Download all data in a zip file.

Part I: Distributed Systems and Distributed Computing

Jupyter Notebooks	Slides	Videos
L00: Linux Basics	HTML	1
L01.1: Introduction to Distributed Computing L01.2: Introduction to Hadoop	HTML HTML	1, 2, 3, 4 1
L02.1: Understanding MapReduce L02.2: MapReduce with Hadoop Streaming	HTML HTML
L03.1: Statistics with Hadoop L03.2: Statistical Modeling with MapReduce	HTML HTML
L04: Distributed Databases	HTML
L05.1: Introduction to Spark L05.2: Datasets and Parallelization in Spark	HTML HTML
L06.1: Structured Data Processing with Spark L06.2: Working with Spark DataFrame	HTML HTML
L07.1: Machine Learning with Spark L07.2: Text Processing with Spark	HTML HTML
L08.1: Introduction to Spark Streaming L08.2: Spark Streaming in Details	HTML HTML
L09.1: Introduction to Scala L09.2: Scala for Spark	HTML HTML	1 2