Full-Stack Deep Learning with Python
With Janani Ravi
Liked by 5 users
Duration: 2h 35m
Skill level: Advanced
Released: 3/24/2026
Course details
Full-stack deep learning encompasses the complete lifecycle of building and deploying machine learning systems—from project planning and data preparation to model training, optimization, and deployment. In this course, join data engineer Janani Ravi as she explores each stage of the lifecycle in Python, using MLflow for MLOps and Optuna for hyperparameter tuning. Learn how to manage machine learning artifacts and environments for reproducibility and scalability, and practice deploying models to serve real-world applications. Upon completing this course, you’ll be equipped with the skills you need to automate and optimize machine learning processes and build full-stack deep learning systems from end to end.
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Skills you’ll gain
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Meet the instructor
Contents
What’s included
- Practice while you learn 1 exercise file
- Test your knowledge 5 quizzes
- Learn on the go Access on tablet and phone
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