Shulou(Shulou.com)06/03 Report--

The primary task of learning big data analysis and application courses is to understand the effects of statistical and modeling methods and data mining methods, and then learn Excel data processing and programming, MySQL database simple operations and basic knowledge of Hadoop. Thus lay a good foundation for advancement and improvement.

basis

Statistical and modeling methods demonstration

Exploratory Data Analysis Demo

Common probability distributions and progressivity demonstrations

Confidence Intervals and Hypothesis Testing Demonstration

Linear Regression Model Demonstration

Generalized linear regression model demonstration

Data Mining Method Demo

Basic flow demonstration of classification prediction

Data Preprocessing Demo

Classification method demonstration

Cluster Analysis Demo

Correlation Analysis Demo

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Excel

Excel data processing

Exercise 1 Excel Basics

Exercise 2 Excel Data Visualization

Exercise 3 Excel Functions and Formulas

Exercise 4 Excel Pivot

Exercise 5 Excel Data Analysis

Excel Advanced Programming

Exercise 1 VBA Program Basics

Exercise 2 VBA data types

Exercise 3 VBA Process Control

Exercise 4 VBA Comprehensive Application

MySQL

Mysql database operations

Exercise 1 Mysql Data Manipulation Statements

Exercise 2 Mysql Data Query Statements

Exercise 3 Mysql Data Query Advanced Statements

Exercise 4 Mysql Views and Indexing

Hadoop Architecture and Fundamentals

Hadoop installation

Exercise 1 Hadoop Installation Environment Configuration

Exercise 2 Hadoop Standalone Mode Installation

Exercise 3 Hadoop Pseudo-Distributed Mode Installation

Exercise 4 Hadoop Fully Distributed Mode Installation

HDFS Principle and Operation

Exercise 1 Reading HDFS File Contents-Example 1

Exercise 2 Reading HDFS File Contents-Example 2

Exercise 3 Reading HDFS File Contents-Example 3

MapReduce Principle and Implementation

Exercise 1 Find the lowest temperature of the year

EXERCISE 2 AVERAGE THE TEMPERATURE

Hadoop Development Example-Sorting with MapReduce

EXERCISE 1 Find the total wage for each department

Exercise 2 Find the number of people and average wages in each department

MapReduce word frequency statistics

Exercise 1 MapReduce Word Frequency Statistics

iterative MapReduce program development

Exercise 1 MapReduce Program Development

Hadoop-HA deployment and usage

installation preparation

Exercise 1 Configuring Hosts

Exercise 2 Installing JDK and Building Zookeeper Clusters

Install Hadoop Cluster

Exercise 1 Installing a Hadoop Cluster

Eclipse connects Hadoop to run mapreduce programs

Exercise 1 Eclipse Connect to Hadoop Run MapReduce Program

(1) Statistical and modeling methods of data and methods of data mining

With the demonstration teaching mode, complete a complete set of processes such as data aggregation, statistics, modeling, analysis and mining, so that students can intuitively master the common methods and processes of big data analysis and application.

(2) Excel data processing methods

Data analysis work ranked fifth in popularity (published by consulting firm Kdnuggets), no basic requirements for students, Excel is one of the components of Microsoft Office series of office software, it is a powerful spreadsheet program. Excel can not only present neat and beautiful tables to users, but also can be used to analyze and predict data, complete many complex data operations, and help users make more informed decisions. At the same time, it also has a powerful visualization function, which can express the data in the table through various graphs and charts, and enhance the expression and appeal of the table. In Excel, some advanced functions of data analysis need to master VBA to be fully realized. Excel is therefore the most basic software tool for data mining and data analysis.

(3) MySQL database basic use methods and basic programming methods

Ranked third in popularity of data analytics (published by consulting firm Kdnuggets), it is very common for small and medium-sized website development due to its small size, fast speed, low total cost of ownership, and especially the advantages of open source. The experiment has no basic requirements for students, but can master the basic methods of using MySQL database and SQL programming.

(4) Knowledge learning of Hadoop architecture and environment building

As the cornerstone of the entire big data ecosystem, Hadoop ranks seventh in the popularity of data analysis, and its knowledge of architecture and environment construction must be learned. Based on HDFS, Hadoop installation, HDFS principle and operation, MapReduce principle and implementation, iterative MapReduce program development are described. Through this lab, students can master common methods and processes for big data analysis with Hadoop.

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