How I got my TensorFlow Developer Certification (Finally!) | by Christine Tee | Jan, 2024

My initial pursuit of the TensorFlow Developer Certification began in 2022, but I ultimately achieved it in 2023. It was a rewarding journey filled with learning and challenges.

While I wouldn’t call myself a Machine Learning guru, I wasn’t exactly a TensorFlow novice when I signed up for the certification. That’s why I skipped the beginner tutorials and went straight for the certification prep.

My primary study material include the TensorFlow Handbook for the certification exam. This official resource provided a solid foundation in all the essential concepts. The skills checklist proved particularly helpful in understanding the expected level of expertise.

Additionally, I enrolled in the Udemy course named TensorFlow Developer Certificate in 2023: Zero to Mastery. This intensive course offered in-depth explanations, hands-on projects, and practice questions, all aligned with the exam syllabus. While I purchased it for RM69.90 during a sale, keep an eye out for frequent Udemy discounts. Here’s why I recommend this course:

  • Comprehensive Curriculum: It covered all the necessary topics, including TensorFlow fundamentals, deep learning concepts, computer vision, NLP, and time series analysis, ensuring readiness for any question.
  • Hands-on Approach: The course emphasizes practical learning through numerous projects and exercises.
  • Community Support: A large and active Discord community of learners and instructors provided Q&A support and a network of peers for encouragement and guidance.
  • Exam Preparation: The course includes dedicated sections on exam tips and practice questions, increasing your chances of success and giving you the confidence to ace the exam.
TensorFlow Developer Certificate in 2023: Zero to Mastery

Remember to factor in the exam cost (USD100, converts to RM445.40 in my country) and ensure you have a government-issued ID for verification.

Credit Card Transaction of the Certification Fees

Before purchasing the exam coupon, verify your information and take a photo for identity confirmation. Once you start the exam, expect a five-minute wait while TensorFlow sets up the environment.

Provisioning Examination Environment

The exam utilizes the latest PyCharm version, and GPU performance can be a significant advantage. If you’re using Windows (like I do), make sure to properly configure CUDA, cuDNN, and TensorFlow within PyCharm.

Important Exam Details:

  • Passing score: 90% (requires full marks on 4 out of 5 questions)
  • Duration: 5 hours (you can finish earlier)
  • Retake policy: 14-day wait for the second attempt, 2-month wait for the third, and 1-year wait after three attempts.

Essential Tips:

  • Read questions carefully: Avoid modifying provided code or variables and refrain from using prohibited functions, as this will lead to immediate failure or 0/5!
  • Practice coding: The hands-on projects in the Udemy course and similar resources are invaluable for solidifying your understanding and applying theoretical knowledge to real-world scenarios.
  • Manage time effectively: Five hours might seem generous, but allocating time wisely for each question is crucial.
  • Don’t give up: Failing the first or even second attempt is common. I personally took many tries to get 5/5 on one of the questions, just keep an eye on the timer!

Don’t let the ‘developer certification’ in the title intimidate you. It’s designed for students or aspiring developers, not just AI gurus. With hard work and dedication, you can unlock TensorFlow Developer Certification too.

Email Received Upon Passing Exam

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