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WIZAPE
Apprentice Mode
10 Modules / ~100 pages
Wizard Mode
~25 Modules / ~400 pages

Data Analytics for Industrial IoT
( 24 Modules )

Module #1
Introduction to Industrial IoT
Overview of Industrial IoT, its applications, and benefits
Module #2
Data Analytics Fundamentals
Introduction to data analytics, types of analytics, and key concepts
Module #3
IoT Data Sources and Types
Overview of IoT data sources, types, and formats
Module #4
Data Ingestion and Storage
Methods for ingesting and storing IoT data, including data lakes and warehouses
Module #5
Data Preprocessing and Cleaning
Techniques for preprocessing and cleaning IoT data
Module #6
Data Visualization for IoT
Introduction to data visualization techniques for IoT data
Module #7
Descriptive Analytics for IoT
Using descriptive analytics to understand IoT data distributions and patterns
Module #8
Predictive Analytics for IoT
Using predictive analytics to forecast IoT data trends and outcomes
Module #9
Machine Learning for IoT
Introduction to machine learning concepts and applications for IoT
Module #10
Anomaly Detection in IoT
Techniques for detecting anomalies and outliers in IoT data
Module #11
Condition-Based Maintenance
Using data analytics for condition-based maintenance in industrial settings
Module #12
Predictive Maintenance
Using data analytics for predictive maintenance in industrial settings
Module #13
Quality Control and Assurance
Using data analytics for quality control and assurance in industrial settings
Module #14
Supply Chain Optimization
Using data analytics for supply chain optimization in industrial settings
Module #15
Energy Management and Optimization
Using data analytics for energy management and optimization in industrial settings
Module #16
Real-Time Analytics for IoT
Streaming analytics and real-time processing for IoT data
Module #17
Edge Computing for IoT Analytics
Deploying analytics at the edge for IoT devices
Module #18
Cloud-Based IoT Analytics
Deploying analytics in the cloud for IoT data
Module #19
Security and Privacy in IoT Analytics
Ensuring security and privacy in IoT analytics deployments
Module #20
Case Studies in Industrial IoT Analytics
Real-world examples of IoT analytics in industrial settings
Module #21
Best Practices for IoT Analytics
Best practices for deploying and maintaining IoT analytics systems
Module #22
IoT Analytics Tools and Platforms
Overview of popular IoT analytics tools and platforms
Module #23
Data Science for IoT Analytics
Applying data science principles to IoT analytics
Module #24
Course Wrap-Up & Conclusion
Planning next steps in Data Analytics for Industrial IoT career


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