Google Certified! Get TensorFlow Developer Certification

Challenge yourself to become a Google Certified TensorFlow Certified Professional!

[Important Notice]

The official Google TensorFlow website has updated information about the certification exam .

If you haven't checked it yet, please make sure to check the information below!

1. The Google TensorFlow Certification Exam is undergoing a reorganization and registration for the current exam will be closed until April 30, 2024 .

2. Registration for the exam is possible until April 30, 2024 , but the exam can be taken until May 31, 2024 .

3. Therefore, those who wish to acquire the certificate must complete registration by April 30, 2024 , and use the registered voucher to take the exam by May 31, 2024 .

4. Those who have not registered for the exam by April 30, 2024, will not be able to take the pre-revised version of the exam and will have to take the updated version. Since no separate announcement has been made regarding the revised version, it's difficult to provide specific dates for when the exam will be available. We will update this page with any new information.

[Main Timeline]

- Exam payment (registration) date: April 30, 2024 (We recommend registering by the 29th to ensure sufficient time)

- Final exam date: May 31, 2024

[Required Documents for Exam Payment and Registration]

- Passport with unexpired validity period or English driver's license

- Exam fee $100

[Official website content]

Link: https://www.tensorflow.org/certificate?hl=ko

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Cumulative Successful Applicants: 679! (Updated April 25, 2024)

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New Exam Questions and Answers Lecture Updated! (As of June 1, 2023)

Participating companies.

Online lectures + 24/7 Q&A channel (Slack).

• We host Q&A in our 24/7 Slack community.
• Through a closed community, students continue to network with each other.

This is Korea's first and most proven lecture . We've analyzed past exam questions with our data analysts and updated the study content to reflect the new formats.

TensorFlow 2.0 certification.

TensorFlow 2.0, developed by Google, is the world's most widely used deep learning library . Google launched the TensorFlow Developers Certificate on March 12, 2020 .

Benefits of certification.

1. You can get recognition from the official global TensorFlow community .
2. You can officially list it on your resume, Github, and LinkedIn (you'll receive a digital badge).
3. Your name will be officially published on the TensorFlow Certificate Network .
4. I receive several contacts a day from overseas headhunters through LinkedIn. I also receive friend requests from people who have obtained TensorFlow certifications, and I'm building a strong network .
5. Of course, it will also be helpful to those looking for new career opportunities in domestic companies.

TensorFlow Certification Exam.

• Examination fee : USD $100 (credit card payment)
• Exam time: 5 hours total
• Test method: Online
• Validity period: 36 months
• What to bring: Passport or English driver's license, selfie (laptop webcam)
• Testing environment: Internet environment, personal laptop, PyCharm IDE, etc.
• Libraries: TensorFlow 2.0, Numpy, etc.

Restrictions on viewing.

• If you fail the first time, you must wait 14 days before retaking the test.
• If you fail the exam for the second time, you can take the exam after 2 months.
• If you fail the exam for the third time, you can take the exam after one year.

Knowledge requirements for taking the TensorFlow certification exam.

Building and Training Neural Network Models with TensorFlow 2.x You should understand the most important and fundamental principles of machine learning (ML) and deep learning (DL) using TensorFlow 2.x.

You should be able to:

• Leveraging TensorFlow 2.x.
• Build, compile, and train machine learning (ML) models using TensorFlow 2.x.
• Preprocessing data so that it can be utilized in the model.
• Predicting outcomes using models.
• Building sequential models with multiple layers.
• Building and training a model for binary classification.
• Building and training a model for multiclass classification.
• Plot loss and accuracy of the trained model.
• Prevent overfitting by identifying strategies including scaling and dropout.
• Leveraging trained models (transfer learning).
• Feature extraction from pre-trained models.
• Verify that the input values to the model are in the correct format.
• The input form of the test data and the neural network must be consistent.
• The output data of the neural network must be able to match the specified input form of the test data.
• Understanding large data loads.
• Trigger the end of the training cycle using a callback.
• Leverage datasets from multiple different sources.
• Leverage datasets in various formats, including JSON and CSV.
• Using datasets from tf.data.datasets.

I was the "second in the Republic of Korea" to obtain it.

If you pass, you will be notified of your acceptance via email.

We'll also send you a questionnaire for official database registration. You'll usually receive a notification of acceptance within a minute .

I'm a "non-major." If I can do it, you can too.

Hello. I'm Lee Kyung-rok, who will be giving the lecture.
I worked as a software developer at Samsung Electronics, and then became independent through the company's in-house venture system.

While researching voice noise removal technology, I had the opportunity to study machine learning/deep learning algorithms. And I fell in love with their allure .
I have a vague belief that future technological trends will focus on artificial intelligence .

However, at the time, there weren't many educational institutions, so I had to diligently study on my own. Through trial and error, online YouTube lectures, and expert help, I was able to build my skills.

Currently, I am establishing Brain Crew Inc. and developing the online education platform Learn A Day (https://learnaday.kr) .
I would like to help those who are struggling with similar issues as I did by producing many good lectures.

The GitHub repo titled "Try Machine Learning on Your Own" has been starred by many people.

I also run a data analysis blog called Teddy Note , which receives approximately 25,000 visitors per month.

Currently, Fast Campus is also offering the "Python Data Analysis All-in-One Package for Working Professionals Online" course.

Since you've read my story, you know that I understand the beginner/non-specialist's perspective better than anyone else.
I'll explain everything from a complete beginner's perspective. Please don't ever think, "Is it okay to ask this?" Feel free to ask anything .

Just know this!

• This course is not designed to make you a deep learning expert.
• In other words, since it is composed solely of content for obtaining certification , it does not matter if you do not have an understanding of TensorFlow or deep learning frameworks.
• I will give you a short and concise lecture to help you obtain your certification in a short period of time .

Frequently Asked Questions.

If you have become interested in obtaining a certificate after taking this course, we will inform you about follow-up courses .

Hands-on training using Colab.

We use Google Colab in class!!

Related blogs and training reviews

• Tensorflow Developer Certification Exam and How to Obtain It
• TensorFlow Certification Course (Offline)
• TensorFlow Certification Course (Zoom Live)
• [Seoul National University] TensorFlow Developer Course