TensorFlow is a widely-used platform that has managed to become a trending competition among its associates. Thanks to all the capabilities it offers, the computations of deep learning and machine learning are eased. The multitude of benefits it offers has made it a top priority for several employers. That is why TensorFlow certifications have become popular as well. Before we dive into the benefits of TensorFlow certification, let’s first understand what TensorFlow is.


TensorFlow is an open-source platform that is ready for any system development and is available for all the users around. With its graphical approach, it is able to offer a better method of data visualization. TensorFlow also allows easy node debugging. This decreases the efforts required for visiting the code and resolving the neural network effectively. TensorFlow is also compatible with Keras because of which users are able to code high-level functionality sections. Keras offer system-specific functionality to TensorFlow such as estimators, pipelining, and eager execution. The functional API of Keras also supports several topologies with different layers, inputs, and output combinations.

You can perform almost every operation using this platform. It is known for its characteristic ability to be deployed on every machine. The model’s graphic representation ensures that the users are able to develop any form of system with the help of TensorFlow. It is this capability that has allowed TensorFlow to develop systems like Intel, Dropbox, Snapchat, Airbnb, etc. It is also compatible with other languages like Python, Ruby, JavaScript, C++, C#, and Swift. So, the user can work in any environment that they are comfortable in.

Thanks to the parallelism of work models, TensorFlow can be used as a hardware acceleration library. Different distribution strategies are used in the CPU and GPU systems. A user is able to choose whether they want to run their code on either architecture on the basis of the modeling rule. If it is not satisfied, the system will choose the GPU. This process decreases the memory allocation as well.

TensorFlow comes with its architecture TPU that can perform computations faster than CPU and GPU. Models that are built using TPU are easily deployed on a cloud and executed at a faster rate. Deep Learning can also use TensorFlow for development as the latter allows building neural networks using graphics that represent an operation as a node. In such cases, TensorFlow will be acting in multiple domains including image recognition, motion detection, voice detection, etc. So, whatever the requirement of the user is, TensorFlow will be able to suit it.

Benefits of TensorFlow Certification

With all the advantages it offers, it is safe to say that TensorFlow will be on the market for a long time. So, getting a certification in the field can be a step in the right direction. Earning the TensorFlow certification will take some money and time. Having the certification is more about posting it on the wall or carrying a card in the wallet. If you are wondering about what you will get in return for your investment, here are some of the benefits of the TensorFlow certification:

  1. Proving your knowledge and skills

Through TensorFlow certification, you will have a way of proving to your current or potential employer that you have the required skills. During the certification program, you will not only be learning about TensorFlow but also how to approach a problem. For example, during your program, you might have to work on some case studies that require you to use your hands-on skills to perform specific tasks.

  1. Remaining competitive and employable

According to CompTIA’s HR Perceptions of IT Training and Certification study, 90% of the employers see certifications as an indicator of a good candidate during the recruitment process. This is because they know that certifications can set a benchmark level for the skills, abilities, and knowledge that they want in their employees. If you are looking for a job, having a certification might give you an upper-hand over your non-certified counterparts.

  1. Gaining proficiency quickly

Many people apply for positions that offer growth opportunities. This means that they might not have the required skills during the time of the hire. Preparing and earning the TensorFlow certificate is a great way of improving your skills and moving up quickly. During the program, you will be taking classes, completing online training modules, and reading a study guide so that you can gain all the required skills. If you go for an online course, you will be able to implement what you have learned on the job as well. In the end, the certification exam will be a validation of your newfound knowledge and skills.

  1. Making an investment

Earning your TensorFlow certification won’t be easy. It will take a lot of time to prepare and cost some money. It doesn’t matter whether you or your company is paying for the course, getting the certification will show that you are invested and interested in your professional development. Also, TensorFlow certification can help you earn more as well.

  1. Keeping your skills up-to-date

Accredited certifications help you remain at the top of your game by making you update your skills. Apart from the course, you can also write for blogs, participate in webinars, and attend conferences for staying updated with the latest advancement in the field and sharing your knowledge with similar minds. This will not only help in keeping your credentials current but also show potential employers that you are passionate and want to continue learning to become better.

Whether you have just started using TensorFlow or have been working with it for years, earning the TensorFlow certification will help you prove your skills and move up the career ladder. 


Please enter your comment!
Please enter your name here