Building TinyML Pipelines Training in Liverpool

Building TinyML Pipelines Training in Liverpool, United Kingdom

This course focused on designing, training, deploying, and operating machine learning models on ultra-low-power, resource-constrained devices such as microcontrollers and edge sensors.

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Building TinyML Pipelines Training is a professional training program delivered by ProgNXT in Liverpool, United Kingdom. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this Building TinyML Pipelines Training course with hands-on, instructor-led sessions. The Building TinyML Pipelines Training is a hands-on, practical program focused on designing, training, deploying, and operating machine learning...

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: HUQ81
14 Hrs
Last Updated: April 2026

Course Rating5/5

The Building TinyML Pipelines Training is a hands-on, practical program focused on designing, training, deploying, and operating machine learning models on ultra-low-power, resource-constrained devices such as microcontrollers and edge sensors.

Participants will learn how to build end-to-end TinyML pipelines—from data collection and model training to optimization, deployment, and lifecycle management—enabling real-time intelligence at the edge for IoT, industrial, wearable, and embedded systems.

Welcome to the official Building TinyML Pipelines Training certification program in Liverpool, United Kingdom. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic programming knowledge (C/C++ or Python helpful)
Familiarity with embedded systems or IoT concepts (recommended)
Introductory understanding of ML concepts is helpful
No advanced deep learning background required

By the end of this training, participants will be able to:

Design complete TinyML pipelines for edge devices
Collect and prepare sensor data for TinyML
Train and optimize models for microcontrollers
Deploy and run ML inference on constrained hardware
Manage updates, monitoring, and lifecycle of TinyML systems
Apply TinyML to real-world embedded and IoT use cases

TinyML system architecture
Sensor data collection and preprocessing
Model training for embedded AI
Model compression and optimization
Microcontroller deployment
Edge inference and monitoring
Embedded AI lifecycle management

TinyML pipeline design
Data preprocessing and feature extraction
Model optimization and deployment
On-device inference performance
Lifecycle and update strategies

Participants who attend all sessions and successfully complete the course assessments will receive a ProgNXT Certificate of Completion.

Introduction to TinyML & Edge AI

What is TinyML and why it matters
TinyML vs traditional edge and cloud ML
Benefits of on-device inference
Common TinyML use cases and limitations

TinyML Pipeline Architecture

End-to-end TinyML workflow
Data → model → deployment → inference loop
Cloud + edge collaboration patterns
Designing for low power and low memory

Sensor Data Collection & Labeling

Types of sensors for TinyML
Streaming and batch data capture
Data labeling strategies
Handling noise and sensor drift

Data Preprocessing for TinyML

Feature extraction for time-series and signals
Windowing and segmentation
Normalization and scaling
Reducing data size for embedded use

Model Selection for TinyML

Choosing lightweight model architectures
Trade-offs between accuracy and footprint
Classical ML vs small neural networks
Model complexity vs device constraints

Training TinyML Models

Training workflows on PCs/cloud
Validation and testing strategies
Preventing overfitting on small datasets
Performance metrics for TinyML

Model Optimization & Compression

Quantization techniques
Pruning and weight sharing
Reducing memory and compute footprint
Balancing latency, accuracy, and power

Deployment to Microcontrollers

Converting models for embedded deployment
Integrating models into firmware
Memory mapping and resource allocation
Build and flash workflows

On-Device Inference & Optimization

Running inference on constrained hardware
Measuring latency and power usage
Real-time vs batch inference
Debugging on-device ML behavior

Edge-to-Cloud Integration

Sending inference results to the cloud
Remote monitoring and logging
Device fleet management concepts
Feedback loops for model improvement

Updating & Managing TinyML Pipelines

Model update strategies
Versioning and rollback
Continuous improvement cycles
Managing model drift at the edge

Security & Reliability for TinyML

Securing models and firmware
Protecting intellectual property
Safe and reliable inference
Fault tolerance on embedded devices

Hands-on Exercises

Summary and Conclusion

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will be evaluated based on: Daily quizzes, mock questions and query resolution. Group Discussion and Case Study Discussion. Assessment will be through hands-on labs, quizzes, and hands-on exercises.

ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

Building TinyML Pipelines Training Events in liverpool

Online Events

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More Upcoming Session Dates

October 2026

🌐 Online Instructor-Led

27th Oct 2026→28th Oct 2026

November 2026

📍 Liverpool, United Kingdom

3rd Nov 2026→4th Nov 2026

🌐 Online Instructor-Led

4th Nov 2026→5th Nov 2026

📍 Liverpool, United Kingdom

19th Nov 2026→20th Nov 2026

🌐 Online Instructor-Led

28th Nov 2026→29th Nov 2026

December 2026

🌐 Online Instructor-Led

1st Dec 2026→2nd Dec 2026

📍 Liverpool, United Kingdom

12th Dec 2026→13th Dec 2026

🌐 Online Instructor-Led

18th Dec 2026→19th Dec 2026

📍 Liverpool, United Kingdom

20th Dec 2026→21st Dec 2026

Events for other courses in Liverpool, United Kingdom

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Building TinyML Pipelines Training in Liverpool