TensorFlow: Data and Deployment Specialization

Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.
In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data, and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.
WHAT YOU WILL LEARN

Run models in your browser using TensorFlow.js
Prepare and deploy models on mobile devices using TensorFlow Lite
Access, organize, and process training data more easily using TensorFlow Data Services
Explore four advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, and TensorBoard

Coursera

DeepLearning.AI

Data Pipelines with TensorFlow Data Services (Coursera)

CS: Software Engineering Computer Science

Dive into the world beyond modeling with 'Data Pipelines with TensorFlow Data Services.' This course will equip you with the skills to deploy machine learning models effectively and optimize your data pipelines for superior performance. From understanding complex deployment scenarios to leveraging data more efficiently in training models, this specialization is designed to bridge the gap between theory and application.

Aug 31st 2026

4 Weeks

ETL TensorFlow Artificial Neural Networks

Coursera

DeepLearning.AI

Browser-based Models with TensorFlow.js (Coursera)

CS: Software Engineering Computer Science

Embark on an exciting journey to bring your machine learning models into the real world with 'Browser-based Models with TensorFlow.js'. This comprehensive course, part of Coursera's Specialization, will teach you how to effectively deploy ML models in any browser using TensorFlow.js. Learn techniques for handling data within browsers and build a practical computer vision project that recognizes and classifies objects from a webcam.

Aug 31st 2026

4 Weeks

Machine Learning Object Detection TensorFlow

Coursera

DeepLearning.AI

Device-based Models with TensorFlow Lite (Coursera)

CS: Software Engineering Computer Science

Embark on a journey into the practical application of machine learning models with 'Device-based Models with TensorFlow Lite'. This course is designed for those who want to extend their expertise beyond modeling data and delve into deploying ML models in real-world scenarios. You'll learn how to optimize models for mobile devices, execute them on both Android and iOS platforms, and even deploy on embedded systems like Raspberry Pi and microcontrollers using TensorFlow Lite.

Aug 31st 2026

4 Weeks

Machine Learning Android Apps Object Detection

Coursera

DeepLearning.AI

Advanced Deployment Scenarios with TensorFlow (Coursera)

Computer Science

Dive into the complexities of bringing your machine learning models from development to deployment with 'Advanced Deployment Scenarios with TensorFlow'. This course, part of a comprehensive specialization on Coursera, will guide you through four distinct real-world deployment scenarios, equipping you with essential skills to train and implement your models effectively.

Aug 24th 2026

4 Weeks

Software Machine Learning Computer Science

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