15 Free Google Courses to Become a Machine Learning Engineer

Machine Learning Crash Course: This is a self-study guide for aspiring machine learning practitioners. It features a series of lessons with video lectures, real-world case studies, and hands-on exercises. It covers introductory machine learning concepts and is suitable for beginners.

TensorFlow Developer Certificate: Google offers a certification program to demonstrate proficiency in using TensorFlow for building deep learning models. While the certification exam requires payment, Google provides free resources and study materials to prepare for it.

Intro to TensorFlow for Deep Learning: This is a series of free tutorials provided by Google on Coursera. It covers TensorFlow fundamentals and how to use it to build deep learning models.

Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization: This is a series of advanced courses on Coursera that covers various topics in machine learning using TensorFlow on Google Cloud Platform. While some courses in the specialization may require payment, audit options are often available to access course materials for free.

Google Cloud Platform Free Tier: Google offers a free tier for its cloud services, including AI and machine learning tools like Google Cloud AI Platform and BigQuery ML. Users can access these services for free within certain usage limits, allowing hands-on practice with machine learning technologies.

Google Developers YouTube Channel: Google's official YouTube channel for developers features numerous videos and tutorials on machine learning topics, including TensorFlow tutorials, talks from Google engineers, and conference presentations.

Google AI Blog: The Google AI Blog provides articles, research updates, and insights from Google's AI research teams. It's a valuable resource for staying updated on the latest advancements and best practices in machine learning.

TensorFlow Hub: TensorFlow Hub is a repository of pre-trained machine learning models that can be readily used for various tasks. It's a useful resource for learning about different model architectures and experimenting with transfer learning.

Machine Learning Recipes with Josh Gordon: This is a video series hosted by Google Developer Advocate Josh Gordon. It covers various machine learning topics in a beginner-friendly manner, with practical examples and code walkthroughs.

Google Colab: Google Colab is a free cloud-based Jupyter notebook environment that supports machine learning and data analysis workflows. It provides access to GPUs and TPUs for accelerated model training and experimentation.

AI Experiments: AI Experiments is a collection of interactive demos and projects showcasing the creative applications of artificial intelligence and machine learning. It's a source of inspiration and exploration for those interested in the field.

Google Research Publications: Google's research publications offer insights into cutting-edge machine learning research conducted by Google's AI teams. While some papers may be highly technical, others provide accessible explanations of novel algorithms and techniques.

Machine Learning on Google Cloud Platform Quest: This is a series of hands-on labs available on Qwiklabs, covering various aspects of machine learning on Google Cloud Platform. While Qwiklabs requires a subscription for full access, there may be opportunities to access some labs for free during promotional periods.

Google Cloud AI Adventures: This is a series of video tutorials hosted by Google Cloud Developer Advocate Yufeng Guo. It covers practical tips and tutorials for using machine learning services on Google Cloud Platform.

Google Cloud Training: Google Cloud offers a variety of training resources, including documentation, tutorials, and learning paths, covering machine learning services like AutoML, AI Platform, and BigQuery ML. While some courses may require payment, there are often free introductory materials available.