Predictive Maintenance for Industrial Equipment Using IoT Data

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About Course

  • Tech Stack: Python (Scikit-learn, TensorFlow), Apache Spark, Kafka, Hadoop, AWS (S3, EMR, SageMaker), Docker
  • Objective: Develop a predictive maintenance system using IoT sensor data to predict equipment failure in industrial plants. This involves real-time data collection using Kafka, batch processing with Spark, and applying machine learning models to predict equipment downtime.
  • Skills Needed: IoT data handling, distributed processing (Spark, Hadoop), real-time streaming (Kafka), machine learning (TensorFlow), AWS deployment.

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