How to pass the Google TensorFlow certification exam?

In the last few years, Artificial Intelligence and Machine Learning have brought an immense digital transformation. In no time, deep learning has entered most sectors including cybersecurity, healthcare, agriculture, genomics, e-commerce, and the like. With its growing importance, it is providing ample career opportunities.

More and more companies are emphasising machine learning and big data for developing new products and more revenue opportunities. TensorFlow certifications equip the professional to be a part of these lucrative career opportunities.

Now, many students, IT professionals, and developers are directed toward Data Science joining the Big Data Economy and searching more about how to pass the Google TensorFlow certification exam.

They are taking a Google TensorFlow course to polish their skills and interests and learn more about how to pass the Google TensorFlow certificate practice exam. To push bars higher in the AI and ML ecosystem, candidates are deciding to get a TensorFlow Certified Developer.

Explore more: Best 15+ Courses on TensorFlow for Machine Learning Engineer

What is TensorFlow?

TensorFlow is one of the most popular open-source deep learning frameworks that allow pre-processing data, modelling the given data to find patterns, and deploying solutions for problems. It excites students, developers, or data scientists who want to showcase their practical machine-learning skills using TensorFlow.

TensorFlow certification is a foundation for candidates who want to develop and train deep-learning basic models to solve complex problems using TensorFlow. This Google TensorFlow developer certificate exam tests the fundamental knowledge and skills of integrating AI and ML models into tools and applications.

It is not an easy task to learn about how to pass the Google TensorFlow certification exam, clear the Google TensorFlow certification preparation exam and become a Google-certified TensorFlow Developer. You will have to prove your skills on various TensorFlow models which help you with tips on how to pass the Google TensorFlow certification exam. The tested models are applied to the following technologies:

• Computer Vision
• Convolutional Neural Networks (CNN)
• Natural Language Processing (NLP)
• Image and Text Recognition
• Processing Data Analytics and Strategies
• Time Series forecasting

This Google TensorFlow certification exam can be taken by anyone who wants to acquire skills to build machine learning-powered applications or showcase his acquired skills to get hired by a top company.

Also Read: Free TensorFlow Certification Courses

Tips and Advice to Pass the Google TensorFlow Certification Exam

You can easily learn how to pass the Google TensorFlow certification exam and pass the Google TensorFlow certification exam if you work hard and keep a few tips in mind to prepare well for the exam.

Here are a few tips and techniques by developers who have cleared the TensorFlow developer certificate exam:

1. To crack the exam, you should know basic ML concepts such as Time Series, Natural Language Processing, and the like. So, it is advised to clear your concepts and also work on the implementation of concepts.
2. Since it is a practical exam, you are advised to take practice TensorFlow certification exam questions as much as you can. Such mock papers give you an idea about the format and level of questions you may witness in your exam.
3. While practising programming exercises, you should not just fill in the code gaps but write the entire thing yourself.
4. Try to keep playing with models, again and again, using different approaches. If possible, try to prepare libraries for yourself beforehand.
5. And the most important tip is to manage time wisely. Though the Google TensorFlow certification exam is a 5-hour long exam, you should not spend more than 20 minutes on improving your accuracy by 5%.
6. Before sitting for the exam, you should go through the official Candidate Handbook. A thorough reading is recommended to understand the instructions and the set-up environment. Make sure your GPU is working and PyCharm is updated with the latest version. All the packages should meet the exam requirements.
7. Keep trying your hands on PyCharm to get familiar with it. Run some of your codes on it to be comfortable and make sure that your code is running as expected.
8. Most of the models you will train in the exam will benefit from training on a GPU. But if you do not have a GPU at home then you should work smartly. In that case, you should copy-paste the code on a COLAB and run it there. Save the model file, download it on your local machine in the particular directory, and then submit your answer.
9. If you have Windows 10, you are advised to pause all the Automatic Updates before starting the Google TensorFlow certification exam.
10. To score maximum in the submitted model add dropout layers, increase batch size, and train for more epochs. Make sure you plot your models’ learning curves.

Top TensorFlow Certification Courses

To crack the Google TensorFlow certification exam, you will have to work extensively on the basic principles of AI, ML, deep learning, and Big Data Analytics. For this, you are advised to enrol in an online course.

Here is a list of the best online TensorFlow courses that can be taken to prepare well for the exam and the Google TensorFlow certification cost:

1. Intro to TensorFlow for Deep Learning by TensorFlow - Udacity

This Google TensorFlow certificate course is developed by the TensorFlow team itself. It is another TensorFlow online learning course that uses a practical approach to polish the deep learning skills of software developers. The cost of this course attracts candidates the most. It is free of cost. During the 2 months of the learning process, you will be trained to build deep learning models using TensorFlow in mobile devices, browsers, and the cloud.

By the end of this course, you will have a firm grip on advanced techniques and algorithms to create your own AI applications. You will excel at working with large datasets. This free Google tensor flow certification course offers rich learning material with interactive quizzes. To make the most of this course, it is recommended to have prior knowledge of Python syntax including variables, functions, classes, and basic algebra.

2. Introduction to TensorFlow Lite by TensorFlow - Udacity

This is an online intermediate course on TensorFlow offered by Udacity. This certification course will explore various programming languages and the use of TensorFlow Lite for the deployment of deep learning models on mobile devices. In this free course, the learners will be provided with practical training on deep learning model deployment on iOS and Android.

It will also help the learners to get knowledge of various aspects of Tensorflow Lite including its framework required for acing the Google TensorFlow certification exam.

3. DeepLearning.AI TensorFlow Developer Professional Certificate- Coursera

Google itself does not provide any TensorFlow online training material. So, you can rely on Coursera’s TensorFlow in Practice. This Google TensorFlow course is a paid course available and this TensorFlow certificate costs $59 per month with a 7-day free trial.

This Google TensorFlow certificate course is the most relevant and the best TensorFlow course for the exam. It makes you learn every basic detail about TensorFlow and teaches you to handle real-world image data. The duration of this Google TensorFlow certification course may vary from 3 weeks to 3 months, depending upon the learners’ pace.

This four-course programme will help you to prepare for Google TensorFlow certification and earn a shareable certificate after completing all the courses. In this Google tensor flow certificate course, you will learn about all the necessary tools to develop AI-powered applications using TensorFlow. You will gain experience to train neural networks and improve your network’s performance.

You will have the attainability to apply your TensorFlow skills to a variety of projects. Above all, this Google TensorFlow certification course will bring you a step closer to accomplishing Google TensorFlow certification.

4. The TensorFlow Developer Certification Handbook

This free handbook should be your first stop. If compared, this Google TensorFlow course outlines topics like the above-mentioned course on Coursera. Being a free handbook, you can read it any time. The handbook is not very lengthy and can be finished in an hour with a thorough reading.

Some topics might appear alien to you if you are new to machine learning and TensorFlow. To get a better understanding of such topics, you are advised to enrol in any of the TensorFlow certifications mentioned in this list. You can download this book for free.

5. TensorFlow 2.0: Deep Learning and Artificial Intelligence - Udemy

This course is the modified second version since TensorFlow was released. This Google Tensorflow course is designed for both beginners and expert-level students with topics covered in detail. Beginners are advised to go through every lecture but if you are familiar with Numpy you can skip a few lectures.

The course starts with basic machine learning models and ends with state-of-the-art concepts. By the end, you will have an idea of time series forecasting and techniques to do stock predictions. This advanced 2.0 version teaches us to deploy a model with TensorFlow Serving and TensorFlow Lite.

Prerequisites include knowledge of coding in Python and Numpy with a basic understanding of probability and derivatives. This Google TensorFlow certificate course can help a lot in clearing the Google TensorFlow certification exam.

6. Introduction to Deep Learning by MIT

As the name says, it is a foundational course on deep learning algorithms with applications in computer vision, art, games, and robotics. Massachusetts Institute of Technology offers this world-class deep learning course to make students gain hands-on experience in building and training neural networks in TensorFlow.

This free course can take up to 24 hours to finish if you devote 1 hour per lecture and 1 hour to review each. The time duration completely depends on the learner’s pace. Eager learners can go through the entire Google TensorFlow certificate course but advanced learners can go through only the first three lectures as they are the most relevant to the exam.

At the end of this TensorFlow online learning course, you will get to participate in a project proposal competition and get feedback from staff and other industry experts. The enrolled students should have basic knowledge of calculus, linear algebra, and matrix multiplication. Experience in Python would be a plus point but having it is not necessary.

Explore Deep Learning With TensorFlow Courses & Certifications by Top Providers

• Udacity Deep Learning With TensorFlow Courses & Certifications
• IBM Deep Learning With TensorFlow Courses & Certifications
• Edx Deep Learning With TensorFlow Courses & Certifications
• Coursera Deep Learning With TensorFlow Courses & Certifications
• TensorFlow Deep Learning With TensorFlow Courses & Certifications
• Vskills Deep Learning With TensorFlow Courses & Certifications

Conclusion

This is how you can crack the Google TensorFlow certification exam after paying the TensorFlow certification cost. Start working on real projects after completing the course and passing the exam. Thus, you are advised to take any one of the TensorFlow online courses and get started.

If you pass the exam, do not forget to get added to the TensorFlow Certified Developers network. So, what are you waiting for? Gather all the learning material, use online resources, and start preparing for the exam. Stay motivated and keep up the hard work.

With proper preparation, you can easily crack this exam and get a TensorFlow developer salary. Good Luck!