Using Sensors With Your Raspberry Pi
- Offered byCoursera
- Public/Government Institute
Using Sensors With Your Raspberry Pi at Coursera Overview
Duration | 8 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
Using Sensors With Your Raspberry Pi at Coursera Highlights
- Earn a Certificate upon completion
Using Sensors With Your Raspberry Pi at Coursera Course details
- This course on integrating sensors with your Raspberry Pi is course 3 of a Coursera Specialization and can be taken separately or as part of the specialization
- This course focuses on core concepts and techniques in designing and integrating any sensor, rather than overly specific examples to copy
- This method allows you to use these concepts in your projects to build highly customized sensors for your applications
- Lastly, we borrow from the fields of data science, statistics, and digital signal processing, to post-process our data in Python
Using Sensors With Your Raspberry Pi at Coursera Curriculum
Designing Sensors
Introduction to Module 1
Sensor Design Concepts 1 of 3
Sensor Design Concepts 2 of 2
Sensor Design Concepts 3 of 2
Sensor Accuracy
Sensor Precision
Sensor Uncertainty
Sensors and Real-Time Processing
Module 1 Quiz
Calibration Methods
Introduction to Module 2
Calibration Terminology
Sensor Transfer Functions
Analyzing Look-Up Tables in Python
Piece-Wise Interpolated Calibration Data 1 of 2
Piece-Wise Interpolated Calibration Data 2 of 2
Calibration with Polynomial Fit 1 of 3
Calibration with Polynomial Fit 2 of 3
Calibration with Polynomial Fit 3 of 3
Summary of Module 2
Module 2 Quiz
Interface Circuits
Introduction to Module 3
Integrated Sensors
Sensor Signal Flow
Sensor Interface Amplifiers 1 of 3
Sensor Interface Amplifiers 2 of 3
Sensor Interface Amplifiers 3 of 3
Reducing Noise with Filters 1 of 2
Reducing Noise with Filters 2 of 2
Summary of Module 3
Module 3 Quiz
Introduction to Signal Processing
Introduction to Module 4
Time-Domain Sliding Window Filter
Noise Removal with Spectral Filtering
Noise Reduction by Averaging
Revisit Time-Domain Sliding Window Filter
Summary of Module 4
Module 4 Quiz
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