Python数据分析培训课程-中科信软培训中心

课程培训

数字技术培训

MicroSoft培训

Oracle培训

Java培训

机械设计培训

CFD培训

CAE培训

其它开发

华为/华三技术

软考类

Python数据分析(xi)培(pei)训课(ke)程

数据分析课(ke)程目(mu)标：

通过该(gai)课程(cheng)的学习(xi)，学员应能(neng)够掌握python常用的类库(ku)、Django Flask Scrapy Numpy Pandas Matplotlib Sklean等(deng)，熟悉整(zheng)个数(shu)(shu)据(ju)分析的流程，详细讲解数(shu)(shu)据(ju)分析涉(she)及到的技术，通过数(shu)(shu)据(ju)抓(zhua)取数(shu)(shu)据(ju)清(qing)洗(xi) 准备(bei)数(shu)(shu)据(ju) 数(shu)(shu)据(ju)分析模型建(jian)立模型预(yu)测可视化(hua)来展(zhan)现数据分析(xi)结果；能够(gou)通(tong)过学(xue)习本课程熟(shu)练(lian)后续(xu)的工(gong)作中(zhong)数据分析(xi)方(fang)面的工(gong)作任务；

数据分析课程(cheng)大纲：

medium none; border-left: medium none; margin: auto auto auto 5.4pt; width: 403.35pt; border-collapse: collapse; border-top: medium none; border-right: medium none" cellspacing="0" border="1"> windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: windowtext 1pt solid; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="text-align: center; margin: 0pt" align="center">主题

windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: windowtext 1pt solid; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-align: center; margin: 0pt" align="center">内容

windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt">

style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">Django框架讲解(jie) windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 18pt">1. Django 简介 style="text-indent: -18pt; margin: 0pt 0pt 0pt 18pt">2. Django组(zu)件介绍 style="text-indent: -18pt; margin: 0pt 0pt 0pt 18pt">3. Django开始一个(ge)项目练习 style="margin: 0pt 0pt 0pt 32.15pt"> windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt">Flask 框(kuang)架(jia)讲(jiang)解 style="margin: 0pt"> windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">1) Flask简介 style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">2) Flask组(zu)件介绍 style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">3) Flask启动一个项目练习 style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">4) Flask蓝图的(de)使(shi)用 style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">5) Flask结合echart制作分析图表(biao) style="margin: 0pt 0pt 0pt 32.15pt"> windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">Mysql windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: 10.5pt; margin: 0pt">1.Mysql基(ji)本操作语句 style="text-indent: 10.5pt; margin: 0pt">2.Mysql多表(biao)关联查(cha)询 style="text-indent: 10.5pt; margin: 0pt">3.Python操作(zuo)Mysql style="margin: 0pt 0pt 0pt 32.15pt"> windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">综合(he)案例 style="margin: 0pt"> windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">1) Flask通过(guo)ORM操(cao)作Mysql style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">2) Flask结合(he)Mysql制作分析图表 style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">3) 通过页面(mian)进(jin)行数据(ju)增删(shan)查(cha)改 style="text-indent: -18pt; margin: 0pt 0pt 0pt 32.15pt">4) 文件的上传下载 style="margin: 0pt 0pt 0pt 18pt"> windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">Scrapy windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: 10.5pt; margin: 0pt">1.Scrapy讲解(jie) style="text-indent: 10.5pt; margin: 0pt">2.Scrapy组件介绍(shao) style="text-indent: 10.5pt; margin: 0pt">3.css选择器 BeautifulSoup讲解 style="text-indent: 10.5pt; margin: 0pt">4.互联网(wang)网(wang)站的数据(ju)爬取(qu) windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">综(zong)合案例 style="margin: 0pt"> windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">1. 数据清(qing)洗 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">2. 数(shu)据分词 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">3. 关(guan)键词抽取 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">4. 云词(ci)python 实现可视化 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">5. Python操作CSV Excel文件 windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">Numpy Pandas windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">1. numpy的常(chang)用(yong)操作(zuo) style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">2. Pandas数据结构(gou)常用操(cao)作 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">3. Pandas数据(ju)处(chu)理以及绘图(tu) style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">4. Pandas 数据(ju)规整 windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">综合案例 style="margin: 0pt"> windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">1. matplotlib绘图(tu)函数讲解 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">2. Pandas 分组聚合(he) 透视表(biao) 交叉表(biao) style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">3. 综合(he)案例分(fen)析(xi) windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">文本相似(si)度 NLP相关 windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">1. 相似度；tfidf word2vec fastText style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">2. Word2vec训练(lian) style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">3. 文本相(xiang)似度(du)案例； style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">4. FastText文(wen)本分类案例 windowtext 1pt solid; border-left: windowtext 1pt solid; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 117pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="156" valign="top"> style="margin: 0pt"> style="margin: 0pt"> style="margin: 0pt">Sklearn案例(li) windowtext 1pt solid; border-left: #f0f0f0; padding-bottom: 0pt; background-color: transparent; padding-left: 5.4pt; width: 286.35pt; padding-right: 5.4pt; border-top: #f0f0f0; border-right: windowtext 1pt solid; padding-top: 0pt" width="381" valign="top"> style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">1. 线性回(hui)归预测 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">2. K近邻预测鸢(yuan)尾花 style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">3. KMeans聚类分析(xi) style="text-indent: -18pt; margin: 0pt 0pt 0pt 28.2pt">4. 逻辑(ji)回归分类(lei)预(yu)测

以上课程可以根据客(ke)户实(shi)际情况进(jin)行灵(ling)活(huo)调整。

如果您想学习本课程，请预约报名
如果没找到合适的课程或有特殊培训需求，请订制培训
除培训外，同时提供相关技术咨询与技术支持服务，有需求请发需求表到邮箱soft@cctvision.net,或致电4007991916
技术服务需求表点击在线申请

服务特点：
海量专家资源，精准匹配相关行业，相关项目专家，针对实际需求，顾问式咨询，互动式授课，案例教学，小班授课，实际项目演示，快捷高效，省时省力省钱。

专家力量：
中国科学院软件研究所，计算研究所高级研究人员
oracle,微软，vmware，MSC,Ansys，candence,Altium,达索等大型公司高级工程师，项目经理，技术支持专家
中科信软培训中心，资深专家或讲师
大多名牌大学，硕士以上学历，相关技术专业，理论素养丰富
多年实际项目经历，大型项目实战案例，热情，乐于技术分享
针对客户实际需求，案例教学，互动式沟通，学有所获

报名表下(xia)载

点击进入报名表

联系我们更多>>

咨询电话：010-62883247

4007991916

咨询邮箱：soft@cctvision.net