Course Overview
This programme develops advanced capabilities in designing and operationalising machine learning solutions using Google Cloud. It focuses on the full ML lifecycle, from problem framing and data preparation to model deployment, monitoring, and optimisation.
Through mentor-led sessions and practical scenarios, learners will build scalable ML pipelines, automate workflows, and deploy models using tools such as Vertex AI. The course emphasises real-world challenges including handling large datasets, improving model performance, and ensuring production reliability.
Aligned with the Professional Machine Learning Engineer certification, this programme also introduces generative AI capabilities, responsible AI practices, and modern MLOps strategies, preparing learners to deliver business-ready AI solutions.
Hands-On Learning
Build ML pipelines, deploy models, and monitor performance using Google Cloud tools.
Mentor-Led Sessions
Delivered by ML engineers with real-world cloud AI implementation experience.
Career-Ready Skills
Develop production-ready machine learning and MLOps expertise.
Learning Outcomes
Design scalable ML architectures
Analyse datasets for model development
Implement ML pipelines using MLOps
Evaluate model performance and fairness
Lead deployment of AI solutions
Communicate ML insights to stakeholders
Prerequisites
Basic programming knowledge (Python/SQL)
Understanding of machine learning concepts
Familiarity with cloud platforms
Detailed Syllabus
Organized by professional domains with comprehensive coverage
Topics Covered:
- •Business problem translation
- •ML vs rule-based approaches
- •Success metrics definition
Skills You'll Gain
Master these in-demand skills through hands-on practice
Career Progression
A clear view of the roles this programme supports, what typically comes next, and where learners progress over time
Ways to Learn
Choose the learning format that works best for you and your team
Live Online
Instructor-Led Training
Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- Live instructor interaction (real-time)
- Trainer-led walkthroughs and real examples
- Guided resources and session notes provided
- Structured Q&A and practical discussion
Price per person
Group enrolments and early planning options available.
All prices are exclusive of VAT where applicable. Group enrolments and custom packages available on request.
Prefer a Faster, Personalised Route into IT?
Not everyone learns best in a group. If you want focused guidance, faster clarity, and confidence you can use on the job, our 1-to-1 Fast-Track Training gives you private, mentor-led support tailored to your experience and goals.
"Many learners choose 1-to-1 when they want understanding, not memorisation."
Exam & Certification Information
Everything you need to know about the certification exams
Important Information
This programme is aligned with the official exam objectives. Exam registration and certification are managed directly by the awarding body.
Credential
Certificate of Completion
On successful completion of Google Professional Machine Learning Engineer (GPMLE) Training, learners receive an Xcademia Certificate of Completion. This standalone certificate is issued directly by Xcademia and is aligned with globally recognised frameworks and best practices.
Frequently Asked Questions
Everything you need to know about this course
No, this is a professional-level course requiring prior ML and programming knowledge.
Ready to Start Your Learning Journey?
Take the next step in your professional development