Deploy Models with TensorFlow Serving and Flask

Course Overview

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
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What skills and knowledge will you acquire during this course?
By taking this course, learners will acquire the skills and knowledge to deploy TensorFlow models using TensorFlow Serving and Docker, as well as create a simple web application with Flask to serve as an interface to get predictions from the served TensorFlow model. Learners should have prior knowledge of Python, TensorFlow, Flask, and HTML in order to be successful in this project. The course runs on Coursera's hands-on project platform called Rhyme On Rhyme, where learners can do projects in a hands-on manner in their browser. Learners will get instant access to pre-configured cloud desktops containing all of the software and data needed for the project. Access to the cloud desktop is limited to five times, but learners will be able to access instructions and videos as many times as they want. This course works best for learners who are based in the North America region, but Coursera is working on providing the same experience in other regions.
lHow does this course contribute to professional growth?
This course provides professionals with the opportunity to gain valuable skills in deploying TensorFlow models using TensorFlow Serving and Docker, as well as creating a simple web application with Flask. By completing this project-based course, professionals will gain the knowledge and experience necessary to deploy TensorFlow models in a production environment. Additionally, the course provides a hands-on approach to learning, allowing professionals to gain practical experience in a cloud desktop environment. This course is an excellent opportunity for professionals to expand their skillset and grow professionally.

Is this course suitable for preparing further education?
This course is suitable for preparing further education as it provides learners with the necessary skills to deploy TensorFlow models using TensorFlow Serving and Docker, as well as create a simple web application with Flask. Learners should have prior knowledge of Python, TensorFlow, Flask, and HTML in order to be successful in this project. The course runs on Coursera's hands-on project platform called Rhyme On Rhyme, and learners will get instant access to a cloud desktop with pre-installed software and data. Learners will be able to access the cloud desktop 5 times, and instructions and videos as many times as they want. This course works best for learners who are based in the North America region.