IoT Data Analytics → Anomaly detection concepts and predictive insights.

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Introduction to IoT Data Analytics
1
- 1.1
  Nature of IoT data, data flow, and analytics objectives.
IoT Data Ingestion & Storage
1
- 2.1
  Streaming data, databases, and time-series storage concepts.
Data Cleaning & Preprocessing
1
- 3.1
  Handling missing data, noise filtering, and normalization.
Exploratory Data Analysis (EDA)
1
- 4.1
  Data exploration, trends, and basic statistical analysis.
Analytics Techniques for IoT
1
- 5.1
  Rule-based analytics, thresholding, and pattern detection.
Visualization & Dashboards
1
- 6.1
  Charts, dashboards, alerts, and reporting.
Advanced Analytics & Anomaly Detection
1
- 7.1
  Anomaly detection concepts and predictive insights.
Real-World IoT Analytics Use Cases
1
- 8.1
  Industrial monitoring, smart cities, and energy analytics.

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