Analytics & ML
Your guide: Data Dora
“Every reading has a time and a cost — decide retention before you decide the database.”
Introduction to Analytics & ML
Anomaly detection, machine learning models, and predictive analytics
Start With the Story
Imagine a field team trying to turn thousands of sensor readings into one defensible next action: warn an operator, tune a model, send less data, or trust an edge device to decide locally. The analytics story starts with that pressure, not with the algorithm name.
Use this module as a route from raw evidence to a decision someone can explain. Each chapter should help you name the signal, shape the data, choose the analysis boundary, and prove why the result is safe enough to act on.
About This Part
This is Part 6.3 of the IoT Class curriculum, which covers analytics & ml topics as part of Module 6: Data.
This section contains 67 chapters exploring:
- Core concepts and fundamentals
- Practical implementations and examples
- Industry best practices
- Hands-on labs and exercises
- Interactive tools and simulations
How to Use This Material
- Navigate: Use the sidebar to browse chapters by topic
- Search: Use the search function to find specific content
- Interactive: Try the embedded simulations and tools
- Practice: Complete the knowledge checks and labs
- Progress: Track your learning journey
Learning Resources
Each chapter includes:
- Comprehensive explanations
- Practical examples
- Interactive demonstrations
- Knowledge check quizzes
- Hands-on lab exercises
Use the sidebar navigation or search to explore topics in this section.