Financial field: fraud detection, credit

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assessment, investment analysis, etc. Medical field: disease diagnosis, drug development, medical image analysis, etc. Scientific research: bioinformatics, astronomy, social sciences, etc. Employment prospects of data mining majors With the advent of the big data era, the demand for data mining talents is increasing. Data mining graduates can find jobs in the following industries: Internet companies: data analysts, algorithm engineers, data scientists, etc.
Financial institutions: risk modelers Email List data analysts, etc. Consulting companies: data consultants, analysts, etc. Government agencies: data analysts, policy researchers , etc. What knowledge do you need to learn data mining? Mathematical foundation: linear algebra, probability theory, statistics. Computer foundation: programming (Python, R, Java, etc. ), databases, operating systems. Machine learning: supervised learning, unsupervised learning, deep learning, etc. Big data technology: Hadoop, Spark, SQL, etc.






How to learn data mining? Systematic learning: You can choose graduate courses in related majors to systematically learn the theory and practice of data mining. Online learning: Coursera, edX and other platforms offer a large number of data mining courses. Self-study: Self-study through books, blogs, open source projects, etc., but you need to have strong self-study ability. Practice: Do more projects and apply theoretical knowledge to practice. Summary Data mining is a field full of challenges and opportunities. If you are interested in data and want to solve practical problems through data analysis, then data mining is a very good choice. To learn more about data mining, you can pay attention to the following aspects: Data mining algorithms: decision trees, random forests , support vector machines, neural networks, etc. Data mining tools: Python (Pandas, NumPy, Scikit-learn), R, Weka, etc.