Google Introduces TensorFlow Developer Certification
Google has launched a certification program for its deep-learning framework TensorFlow. The certification exam is administered using a PyCharm IDE plugin, and candidates who pass can be listed in Google's world-wide Certification Directory.
The new certification was announced in a blog post by TensorFlow program manager Alina Shinkarsky. Candidates are tested on their ability to develop and train deep-learning models using TensorFlow, and problem spaces include computer vision (CV), natural-language processing (NLP), and sequence modeling. The exam fee is $100, and the certification is valid for three years. Certified developers will receive an official certificate and will be entitled to include a badge on their social media pages. According to Shinkarsky,
This certificate in TensorFlow development is intended as a foundational certificate for students, developers, and data scientists who want to demonstrate practical machine learning skills through building and training of basic models using TensorFlow.
The certificate candidate handbook includes more technical details. Models must be built using Python 3.7 and TensorFlow 2.x. The exam runs in the PyCharm IDE using a special plugin and may be taken on any computer that supports the required software and is connected to the internet. Candidates are given five hours to complete the exam and must achieve a score of 90%. Those who do not pass may attempt the exam a total of three times in one year; the exam fee is required for each attempt. During the exam, test-takers must build five deep learning models in the following categories:
- Basic model
- Model from dataset
- Convolutional neural network (CNN) model for real-world image data
- Natural-language processing (NLP) model for real-world text data
- Sequence model for real-world numeric data
Developers who pass the exam can join the Google Developers Certification Directory. The directory also includes engineers who attained two of Google's other certifications: Associate Android Developer and Mobile Web Specialist. Google announced its Google Developer Certification program in 2016, with Associate Android Developer as the first certification. Later that year, Google also launched its certification program for Google Cloud, announcing Certified Professional exams for Cloud Architect and Data Engineer. However, unlike the Google Developer exams, which are "self-service" exams that candidates may take on their own computers, the Google Cloud certifications require proctored exams that are taken at dedicated test centers.
The other leading cloud providers, Amazon Web Services (AWS) and Microsoft Azure, have certification programs similar to the Google Cloud program, and include certifications focused on machine learning and AI. AWS announced its machine-learning specialty exam in late 2018 and Microsoft announced their AI and data science certifications in early 2019. Google Cloud does not have an AI-specific certification.
In a discussion thread on Reddit, one user described his experience with the TensorFlow exam:
I have recently taken the exam on my MacBook Pro 15" with i9 CPU. Having GPU would have been beneficial because it's faster but not I didn't feel that GPU was necessary. If the problem requires a complex model (not really that complex. About 3~5M parameters), about 10 epochs are sufficient which took about less than 10 minutes.
Google does not offer training materials for the certification, but recommends a Coursera specialization, TensorFlow in Practice, for students who wish to prepare for the exam. The Google Developer TensorFlow Certificate site claims that additional certifications are being developed for "more advanced and specialized TensorFlow practitioners," but no timeline has been announced.