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TensorFlow

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TensorFlow


The TensorFlow exam evaluates your proficiency in using TensorFlow, an open-source machine learning framework developed by Google. This exam tests your ability to build and deploy machine learning models using TensorFlow, covering core concepts, practical applications, and advanced techniques.


Who should take the exam?

  • Data Scientists: Professionals looking to validate their TensorFlow skills for building machine learning models.
  • Machine Learning Engineers: Individuals focusing on implementing and optimizing machine learning algorithms.
  • Software Developers: Developers interested in integrating machine learning models into applications.
  • AI Researchers: Researchers seeking a practical understanding of TensorFlow for their projects.
  • Students: Students in data science or AI programs who want to demonstrate their TensorFlow capabilities.


Course Outline

The TensorFlow exam covers the following topics :-

  • Module 1: Introduction to TensorFlow
  • Module 2: Understanding TensorFlow Basics
  • Module 3: Understanding Data Preparation
  • Module 4: Understanding Building Models with TensorFlow
  • Module 5: Understanding Training and Evaluation
  • Module 6: Understanding Advanced TensorFlow Concepts
  • Module 7: Understanding Model Deployment
  • Module 8: Understanding Practical Applications
  • Module 9: Understanding TensorFlow in Production
  • Module 10: Understanding Exam Preparation

TensorFlow FAQs

It will be a computer-based exam. The exam can be taken from anywhere around the world.

You have to score 25/50 to pass the exam.

No there is no negative marking

There will be 50 questions of 1 mark each

You can directly go to the certification exam page and register for the exam.

You will be required to re-register and appear for the exam. There is no limit on exam retake.

The result will be declared immediately on submission.

  • Data Scientists: Professionals looking to validate their TensorFlow skills for building machine learning models.
  • Machine Learning Engineers: Individuals focusing on implementing and optimizing machine learning algorithms.
  • Software Developers: Developers interested in integrating machine learning models into applications.
  • AI Researchers: Researchers seeking a practical understanding of TensorFlow for their projects.
  • Students: Students in data science or AI programs who want to demonstrate their TensorFlow capabilities.

The TensorFlow exam evaluates your proficiency in using TensorFlow, an open-source machine learning framework developed by Google. This exam tests your ability to build and deploy machine learning models using TensorFlow, covering core concepts, practical applications, and advanced techniques.

  • Proficiency in TensorFlow: Advanced understanding and practical skills in using TensorFlow for various machine learning tasks.
  • Model Building Expertise: Ability to design, implement, and optimize neural network models using TensorFlow’s APIs.
  • Data Handling and Preprocessing: Competence in loading, cleaning, and preprocessing data effectively for machine learning applications.
  • Deployment Skills: Knowledge of deploying and managing TensorFlow models in production environments, including using TensorFlow Serving and TensorFlow Lite.
  • Practical Machine Learning Application: Hands-on experience in applying machine learning techniques to real-world problems, such as image classification, NLP, and time series analysis.

Only Multiple-choice questions (MCQ) are asked.