AI-Based Fraud Detection System for FinTech Transactions

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About Course

  • Tools & Languages: Python, R, TensorFlow, PyTorch, Scikit-learn, SQL, Apache Kafka, Power BI
  • Objective: Develop an AI-driven system for real-time fraud detection in financial transactions. Use machine learning models (e.g., anomaly detection, decision trees) to identify fraudulent activities based on transaction patterns. Integrate with a live transaction system using Apache Kafka and visualize insights with Power BI.
  • Skills Needed: Fraud detection algorithms, machine learning (Python, R), real-time data processing (Kafka), anomaly detection, SQL for data management, visualization tools (Power BI).

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