🚀Get Certified: Community Edition are weekly events over 6 weeks designed for people who want to prepare for a Google Cloud certification.

📅 Saturday, August 23, 2025

⏰ 5:00 PM - 7:00 PM GMT+2 time zone

📍 Location: ONLINE

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

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:

• 6 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 are running a 6 week series of events:

week 1 https://gdg.community.dev/e/mb72w7/

week 2 https://gdg.community.dev/e/mjv4yp/

week 3 https://gdg.community.dev/e/myu5as/

week 4 https://gdg.community.dev/e/mjefdy/

week 5 https://gdg.community.dev/e/mv8e45/

week 6 https://gdg.community.dev/e/mzybrt/

#PrepWithGDG #AI #ML