1, Python data analysis: learning Python programming language and its application in data analysis.
2, R language data analysis: learning R language and its application in data analysis.
3. Data visualization: Learn how to use data visualization tools, such as Tableau, PowerBI, QlikView, etc. , converting data into easy-to-understand charts and graphs.
4. Data mining: Learn how to use machine learning and data mining technology to find patterns and trends from a large amount of data.
5. Database management: Learn how to design and manage a database, and how to use SQL for data query and analysis.
6. Basis of statistics: Learn the basic knowledge of statistics, such as probability, hypothesis testing and regression analysis, so as to better understand and apply data analysis techniques.
7. Business Intelligence: Learn how to apply data analysis to business decisions, including data dashboards, reports, forecasts and trend analysis.