🚀Get Certified: Community Edition are weekly events over 8 weeks designed for people who want to prepare for a Google Cloud certification.

🚀 📅 Event Date: June 5, 2026

📍 Location: ONLINE

❗️We will NOT be recording this series of events, so please register for all 8 sessions—this is the only way to receive timely notifications. Furthermore, be sure to attend all 8 events to be fully prepared for the exam!

Join this Study Group to learn more and prepare for the Professional Machine Learning Engineer certification.

Take this opportunity to connect, learn, and drive change in the tech landscape. See you there!

What is the role of a Professional Machine Learning Engineer?

A Professional Machine Learning Engineer builds, evaluates, productionizes, and optimizes AI solutions by using Google Cloud capabilities and knowledge of conventional ML approaches.

• The ML Engineer handles large, complex datasets and creates repeatable, reusable code.
• The ML Engineer designs and operationalizes generative AI solutions based on foundational models.
• The ML Engineer considers responsible AI practices, and collaborates closely with other job roles to ensure the long-term success of AI-based applications.
• The ML Engineer has strong programming skills and experience with data platforms and distributed data processing tools.
• The ML Engineer is proficient in the areas of model architecture, data and ML pipeline creation, generative AI, and metrics interpretation.
• The ML Engineer is familiar with foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance.
• The ML Engineer enables teams across the organization to use AI solutions. By training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable, performant solutions.

This program will provide community members the opportunity to:

• Instructor led workshops
• Support from experts and other fellow developers
• Access to Cloud Skills Boost
• Additional learning material on certificate

Overall Goal:

To prepare participants to build, evaluate, productionize, and optimize AI solutions using Google Cloud capabilities and conventional ML approaches, handle complex datasets, create reusable code, and design/operationalize generative AI solutions, all while considering responsible AI practices.

Important Notes for the Study Program:

• The exam does not directly assess coding skill, but a minimum proficiency in Python and Cloud SQL is needed to interpret code snippets in questions.
• This exam version covers tasks related to generative AI, including building AI solutions using Model Garden and Vertex AI Agent Builder, and evaluating generative AI solutions.

The Certification Study Group offers:

• 8 live sessions to go through certification content and exam questions.
• Online community where you can ask questions and share your knowledge.
• Video courses and hands-on training on Cloud Skills Boost, Google Cloud training platform.

If you want to learn more about other Google Cloud training opportunities offered by Google Developer Groups, please visit this page:

Get Certified: Community Edition

❗️We will NOT be recording this series of events, so please register for all 8 sessions—this is the only way to receive timely notifications. Furthermore, be sure to attend all 8 events to be fully prepared for the exam!

Full list of all 8 Sessions:

Session 1 ML Fundamentals

Session 2 Data on Google Cloud

Session 3 ML on Google Cloud

Session 4 Custom Training in Google Cloud

Session 5 Productionising ML Part 1

Session 6 Productionising ML Part 2

Session 7 Model Monitoring & Explainability

Session 8 Ethics Exam Guide Review & Exam Prep 

Join us on June 5, 2026, and be a part of this empowering session. Secure your spot now and let's innovate for a better tomorrow together! 

#PrepWithGDG #AI #ML