A step by step guide to becoming a TensorFlow Certified Machine Learning Engineer.

With the rise of A.I. also comes the rise of the Data Scientist, or the person behind all these supernatural feats. Simply put, a Data Scientist is an effective machine learning practitioner.

If you want to prove to the world that you are a real data scientist, you will have to pass a 5 hour test administered by Google and Tensorflow.

This exam is not easy, but it is a highly rewarding endeavor in which those who have passed the exam can say they are a part of a very select group of only around 1700 people worldwide! For those of you brave enough looking to attempt this exam, make sure to prepare with the following:

Python Programming

Tensorflow was originally developed for Python users but can support javascript and other languages today. However, you will get the best support and easiest start by learning TF through Python.

Data Science Basics

This includes using pandas for data analysis, matplotlib and seaborn for data visualization, and scikit-learn for creating the classic models of data science from linear regression to support vector machines and clustering algorithms. TPA also offers classes in data science basics.

Online Resources

If you are looking to spend $0 on learning deep learning, we recommend taking the FastAI Youtube series that takes you from beginner to advanced. It does not cover everything however, and you may want to supplement your knowledge with some affordable online resources such as Deeplearning.ai or Coursera.

The exam will cover:

• TensorFlow developer skills

• Building and training neural network models using TensorFlow 2.x

• Image classification

• Natural language processing (NLP)

• Time series, sequences and predictions

In summary, the exam covers all the hardest parts of Machine Learning! Therefore, if you are able to pass this exam, you will prove to the world that you are a proficient machine learning engineer, ready for the rise of A.I. We wish you the best of luck!