How To Pass The TensorFlow Developer Certificate Exam

So, you have decided to get the TensorFlow Developer Certificate. In order to ensure that you pass the certification exam, you need to complete the program and sharpen your skills. But, this is easier said than done. In this article, we will be providing you with the details on passing the TensorFlow Developer Certificate exam.

What Is TensorFlow?

Before we dive into the certificate exam, let’s first discuss what TensorFlow is.

TensorFlow is a popular, open-source numerical computing framework through which you can preprocess and model data and deploy your solutions. Google uses TensorFlow for powering all of its machine learning services. In fact, it is highly likely that the device that you are currently using has run some form of TensorFlow before. In most cases, you will be writing your TensorFlow code in Python or JavaScript (tensorflow.js). Please note that the exam will be in Python. Your TensorFlow code will be triggering a series of underlying C functions that will execute what it has been told to do. This includes a lot of numerical calculations for machine learning development.

What Is the TensorFlow Developer Certification?

Now that you have an idea of what TensorFlow is, let’s move on to the TensorFlow Developer certification and what you should do for it.

The TensorFlow Developer Certification is one of the best ways for you to display your ability to use the framework. More specifically, it shows your ability to use the Python version of TensorFlow for building deep learning models for business that are capable of performing a wide range of tasks like computer vision (searching for patterns in images), time series forecasting (using a range of past events for predicting future trends), natural language processing (searching for patterns in the text), and regression. The exam costs $100 USD.

The most popular reason why you should get the TensorFlow Developer certificate is to upgrade your skills and make yourself more employable. There are two other specific reasons why you need to get certified in TensorFlow:

● Acquire the foundation skills and a tech background for creating machine learning-powered applications.
● Demonstrating your competency and skills to the current or potential employer.

According to recent studies, compared to other frameworks used for deep learning, TensorFlow dominates every other framework.

Passing The TensorFlow Developer Certificate Exam

The TensorFlow Developer certificate exam is an online performance-based test in which you will be given questions that will be solved by creating TensorFlow models that have a dedicated environment. To take this exam, you need a computer that can support the IDE requirements. Also, you will need a reliable and stable internet connection. The best part about this exam is that you can take it at any time that suits you. So, whether you are an early morning bird or a night owl, taking the exam won’t be an issue.

The TensorFlow Developer certificate exam will test your ability to solve problems like using real-world images for Image classifications, using Tensorflow 2.x for time series forecasting, and natural language processing. You will have 5 hours for completing the exam. If you don’t complete the exam within the time limit, it will be auto-submitted. In such cases, you will be graded only for the questions for which you tested and submitted your model. You can use any learning resource that you can normally use while working on your ML development.

In order to prepare for the exam, the first thing that you have to do is study. You will have to dedicate a substantial amount of time to this. There is a comprehensive handbook created by the TensorFlow team that provides you with every single detail about the exam as well as the skills you must have to take it. Of course, you can also use online courses for tech entrepreneurs as well. Once you have studied for the exam, you need to design a curriculum that covers every single skill set mentioned in the handbook. Create a study schedule so that your work engagements don’t push you off track. You have to prioritize studying for at least a month before the exam. Consider this like any other work project and see it through to completion.

Every night, plan what you are about to study the next morning. Dedicating 3 to 4 hours in the morning will be productive for your preparation. It is important to have a consistent routine. As you get close to the day of the exam, you can raise the intensity and practice for 5 to 6 hours every day.

While studying, start by watching the lessons and then practice the code. Make sure that you complete all the assignments. Instead of completing the placeholder code, you should write the entire code yourself. At the end of your time slot or just before sleeping, revisit what you have learned during the day to ensure that everything is crystal clear. Keep this routine up and running until the night before the exam.

Exam Day

Ideally, you should take several steps to prepare for your certification test on exam day. According to AI and ML software development professionals who have obtained the certification, it is helpful to review your notebooks and repositories beforehand. Since the test is open-book, you can save time by familiarizing yourself with your resources’ locations. To start the certification, you simply need to click on “Start Exam” in your IDE. Notably, the grading is often based on five models, with increasing difficulty levels. In the past, Tensor Flow has given individuals five hours to complete the exam. Of course, you can complete it in less time with a proper studying regimen. If you pass your exam, you should receive an email notification shortly after completion.

If you are unsure about preparing for the TensorFlow Developer certificate exam all by yourself, you can enroll yourself in a TensorFlow certification that will help you learn all the required skills and prepare you well for the exam.

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