Which Google Cloud training course to choose?
MFE-IT’s Google Cloud Platform catalog covers the entire GCP journey — from decision-maker level (Cloud Digital Leader, Generative AI Leader) to the Associate and Professional certifications (Architect, Data Engineer, Security, DevOps, Network, Machine Learning), including the data and container building blocks (BigQuery, GKE). This guide helps you choose according to your role, level and specialty. Prices in euros excluding tax; sessions of 1 to 3 participants, on-site or remote.
| Your goal | Training course | Duration | Price |
|---|---|---|---|
| Decision-maker — cloud value | Cloud Digital Leader (CDL) | 1 day | €740 excl. tax |
| Drive generative AI | Generative AI Leader | 2 days | €1,480 excl. tax |
| Big Data & ML fundamentals | GCP100B — Data/ML Fundamentals | 1 day | €780 excl. tax |
| Become operational (Associate) | Associate Cloud Engineer (ACE) | 4 days | €2,960 excl. tax |
| Design architectures | Professional Cloud Architect (PCA) | 5 days | €3,700 excl. tax |
| Data engineering | Professional Data Engineer | 5 days | €3,700 excl. tax |
| Industrialize ML (Vertex AI) | Professional ML Engineer | 3 days | €2,220 excl. tax |
| Analytics & data warehouse | BigQuery | 3 days | €2,220 excl. tax |
| Kubernetes containers | Google Kubernetes Engine (GKE) | 3 days | €2,220 excl. tax |
| Secure Google Cloud | Professional Cloud Security Engineer | 4 days | €2,960 excl. tax |
| DevOps / SRE | Professional Cloud DevOps Engineer | 4 days | €2,960 excl. tax |
| Network & connectivity | Professional Cloud Network Engineer | 4 days | €2,960 excl. tax |
Start with Cloud Digital Leader to understand the value of Google Cloud with no technical prerequisites. To frame generative AI in the enterprise, continue with Generative AI Leader.
Aim for Associate Cloud Engineer to deploy and administer on GCP. For a fast entry into data and machine learning, GCP100B lays the fundamentals.
Professional Cloud Architect is the reference for designing scalable, secure and resilient architectures on Google Cloud.
For data engineering: Professional Data Engineer. For analytics and data warehousing: BigQuery. To industrialize your models on Vertex AI: Professional ML Engineer.
Depending on your specialty: DevOps Engineer (CI/CD, SRE), Network Engineer (connectivity and networking) or Security Engineer (infrastructure and data security).
Google Kubernetes Engine (GKE) teaches you to deploy and operate Kubernetes in production on Google Cloud.
Not sure which Google Cloud course fits your needs?
For every project we run a preliminary interview with our experts to take your level, needs, professional context and goals into account. Explore all our Google Cloud Platform training courses.