TensorFlow Lite

The TensorFlow Lite training is an intensive two-day course focused on the practical application of TensorFlow Lite for deploying AI models on mobile and embedded devices.

Duration

16h · 2 days

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Who it's for

Ideal for teams that…

1 Mobile application developers who want to integrate AI models into their apps

2 Data scientists and ML engineers who want to deploy and optimize models on mobile devices

3 IT specialists who want to use TensorFlow Lite for deploying AI models in resource-constrained environments

Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

How to configure and manage TensorFlow Lite for deploying ML models on mobile devices

✓

How to convert and optimize TensorFlow models into the TensorFlow Lite format

✓

How to deploy and monitor TensorFlow Lite models on Android and iOS

✓

How to integrate TensorFlow Lite with mobile applications and cloud services

Requirements

What you should know before we start

Basic knowledge of Python programming
Basic knowledge of machine learning
Experience in developing mobile applications for Android or iOS

Program

What we actually do

Day 1: Introduction to TensorFlow Lite and Model Optimization

· Introduction to TensorFlow Lite and its architecture
· Installation and configuration of TensorFlow Lite on different platforms
· Converting TensorFlow models to TensorFlow Lite format
· Optimizing models using quantization, pruning, and other techniques
· Practical exercises with conversion and optimization on a real ML model
· Analyzing optimization results
· Overview of TensorFlow Lite libraries for Android and iOS
· Integrating TensorFlow Lite into mobile applications

Day 2: Advanced Techniques and Practical Applications

· Practical aspects of deploying TensorFlow Lite models on Android and iOS
· Handling model inputs and outputs in mobile apps
· Techniques for monitoring model performance on mobile devices
· Debugging and optimizing deployed models
· Practical exercises with deploying a model on a mobile device
· Testing the model in a real mobile application
· Integrating TensorFlow Lite with Google Cloud AI services
· Using CI/CD tools to automate model deployments

Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.

How we work

From brief to retro in 30 days.

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief

✓First session within 30 days

✓Pilot before the full decision

✓VAT invoice, payment in instalments possible

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