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这是为期5天的Data Science和AI入门。
本课程随附使用Python示例和练习
Data Science/AI 简介
- 通过数据获取知识
- 知识表示
- 价值创造
- Data Science 概述
- 人工智能生态系统和新的分析方法
- 关键技术
Data Science 工作流程
- 脆-dm
- 数据准备
- 模型规划
- 模型构建
- Communication
- 部署
Data Science 技术
- 用于原型设计的语言
- 大数据技术
- 常见问题的端到端解决方案
- Python 语言简介
- 将 Python 与 Spark 集成
人工智能 Business
- 人工智能生态系统
- 人工智能伦理
- 如何在业务中推动 AI 的发展
数据源
- 数据类型
- SQL 与否SQL
- 数据存储
- 数据准备
Data Analysis – 统计方法
- 概率
- Statistics
- 统计建模
- 使用 Python 的业务应用程序
机器学习在商业中的应用
- 受监督与无监督
- 预测问题
- 分类问题
- 聚类问题
- 异常检测
- 推荐引擎
- 关联模式挖掘
- 使用 Python 语言解决 ML 问题
深度学习
- 传统 ML 算法失败的问题
- 用 Deep Learning 解决复杂问题
- Tensorflow 简介
自然语言处理
数据可视化
- 建模的可视化报告结果
- 可视化中的常见陷阱
- 使用 Python 进行数据可视化
从数据到决策 – 沟通
- 产生影响：数据驱动的故事讲述
- 影响效果
- 管理 Data Science 个项目
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