项目总时长为12课时,导师与学生线上沟通(布置软件学习等相关的任务,引导学生熟练使用SQL,Python, Streamlit等数据分析和可视化工具),会根据学生基础进行课程调整,知识点梳理和范例讲解,提供给学生数据案例并利用方法包括:数据处理,机器学习和网页App等,最后搭建一个可以放在简历或者Github上的数据分析交互网站。
1
Intro to operational optimization in the context of E-commerce Supply Chain and its applications in Data Science
2
Getting familiar with SQL and Python Query Data with SQL & Exploratory Data Analysis with Python
考察:SQL & Python coding Data analysis
授课4小时; 学习4小时
3
Introduction to Forecasting Models Time series models to forecast customer demand
考察:Build and Analyze different forecast models
授课2小时; 学习2小时
4
Build causal model to improve network transparency Causal inference to connect the supply chain network and identify bottlenecks
考察:Causal Model Building and Inference
授课3小时; 学习4小时
5
Create Interactive Dashboard with Streamlit and Python Streamlit分析模型可视化
考察:Streamlit & Python coding tasks
授课1小时; 学习1小时