TensorFlow with Python Course
This course provides comprehensive training on using TensorFlow with Python to develop robust recommendation systems, covering data preparation, model building, training, evaluation, and deployment.

4 to 360 hours of flexible workload
certificate valid in your country
What Will I Learn?
This TensorFlow with Python Course teaches you to build, train, debug, and evaluate recommendation models from start to finish. You will clean and preprocess real interaction data, design embedding-based architectures using Keras, fine-tune training loops and callbacks, and steer clear of common evaluation errors. Learn to produce predictions, interpret embeddings, and provide clear, reproducible results that stakeholders can rely on.
Elevify Advantages
Develop Skills
- TensorFlow recommender design: build, tune, and regularise high-impact models quickly.
- Data prep for TensorFlow: clean, encode, and engineer features for recommendations.
- Training and debugging: fix exploding gradients, poor metrics, and class imbalance.
- Evaluation mastery: design splits and compute ranking metrics with Python tools.
- Model deployment basics: save, load, explain, and deliver reproducible prediction code.
Suggested Summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.

Giulio CarloPrompt Engineering Student
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