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What is data mining Data mining is a process of extracting implicit knowledge from large amounts of data. It uses statistics, machine learning, artificial intelligence and other methods to discover rules, trends, associations and patterns from massive amounts of data, thereby supporting decision- making and predicting the future. Why learn data mining? Demands in the era of big data: With the explosive growth of data volume, companies are in urgent need of extracting value from data. Wide range of application scenarios: Data mining is widely used in marketing, finance, medical care, e-commerce and other fields. High-paying careers: There is a large demand for data mining talents, and the salary is generous.

Core courses of data mining majors Principles of database systems: Learn about database design, management and query. Data warehouse and OLAP technology: Learn about the construction and multidimensional analysis of data warehouses. Statistics: Learn about Special Data descriptive statistics, inferential statistics, multivariate statistical analysis , etc. Machine learning: Learn about algorithms such as classification, clustering, regression, and association rule mining. Data mining algorithms: In-depth study of the principles and applications of various data mining algorithms. Big data technology: Learn about big data processing platforms such as Hadoop and Spark. Data visualization: Learn to visualize data results for better understanding and presentation.



Employment prospects of data mining majors Data analyst Collect, clean, analyze data, and provide data support. Data scientist: Use data mining technology to solve complex problems and provide decision support for enterprises. Machine learning engineer: Develop and deploy machine learning models. Artificial intelligence engineer: Engage in the research and development of artificial intelligence related products. How to learn data mining? Systematic learning: It is recommended to choose a regular university or training institution for systematic learning. Practical operation: More hands-on practice, familiar with various data mining tools and platforms.