Import pretrained DL models in TensorFlow

Required Prerequisites: Please ensure the following before enrolling in this microcredential:

• Fundamental programming knowledge in Python or similar languages (e.g., C/C++, R, Matlab, Java).
• Basic understanding of linear algebra and statistics is also recommended.

This hands-on course introduces you to importing and adapting pretrained deep learning models using TensorFlow. You’ll explore how to identify suitable models from Keras Applications, TensorFlow Hub, and the Model Garden, then load and inspect them programmatically.

Through interactive coding exercises, you’ll prepare data pipelines that replicate original model preprocessing and apply transfer learning to customize models for your own use cases. Whether you're supporting AI model deployment, optimizing data workflows, or experimenting with deep learning applications, this course equips you with practical tools to move efficiently from concept to implementation.

Key Benefits

• Import models from TensorFlow resources
• Inspect architecture and input requirements
• Build TensorFlow pipelines with real data
• Apply quick transfer learning techniques
• Hands-on coding with real-world examples

This micro-badge is a part of the Deep Learning with TensorFlow Badge.

Program Schedule: Sessions will be held via Zoom:

• Dates coming soon

Micro-badge Level

This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence.

Learn more about the Ira A. Fulton Schools of Engineering micro-badge leveling system.