Google Cloud Training · Architecture, Engineering & Capability Building
Build the skills to put Google Cloud to work.
Help your team move from understanding cloud services to making confident technical decisions. Instructor-led Google Cloud Platform (GCP) training combines architecture discussions, guided demonstrations and hands-on exercises across cloud infrastructure, networking, Kubernetes, data analytics and operations.
Programs are shaped around the people using the platform and the workloads they need to build, manage and improve.
Live Virtual · Classroom · On-Site · Hybrid · Worldwide
Your Google Cloud Trainer
Connect cloud learning with enterprise experience.
Ahmad Majeed Zahoory brings together technology consulting and corporate training to explain how cloud services fit into broader enterprise environments.
His approach connects platform knowledge with architectural reasoning, implementation choices and day-to-day operational responsibilities.
Learn how to evaluate options, understand dependencies and work through practical scenarios with guidance from an experienced technology practitioner.
Google Cloud Training Areas
Understand the platform. Develop the skills your role requires.
Build a learning program around the areas that matter to your organization. Training can begin with Google Cloud essentials or focus on a specific engineering, architecture or operational requirement.
Google Cloud Foundations & Resource Organization
Understand Google Cloud regions, zones and core platform concepts. Explore organizations, folders, projects and billing relationships, and learn how resource organization supports access management and governance.
Cloud Architecture & Design Decisions
Translate business requirements into technical designs. Compare service options, examine managed-service trade-offs and consider reliability, security, performance and cost when designing Google Cloud workloads.
VPC Networking & Hybrid Connectivity
Explore Google Cloud’s global VPC networks and regional subnets. Work through IP addressing, routes, firewall controls, Shared VPC, DNS and load balancing, with discussion of Cloud VPN and Cloud Interconnect for hybrid connectivity.
Identity, Security & Governance
Understand IAM roles, service accounts and resource hierarchy. Explore least-privilege access, organization policies, audit logging and approaches to granting applications access without relying on long-lived service account keys.
Cloud Administration & Operations
Develop operational confidence using the Google Cloud console and command-line tools. Practice resource management, quota awareness, monitoring, logging and troubleshooting across projects and workloads.
Google Kubernetes Engine & Containers
Explore container orchestration with Google Kubernetes Engine (GKE). Work through cluster concepts, workload deployment, service exposure, scaling and operational responsibilities, including considerations when choosing Autopilot or Standard.
Cloud Run & Event-Driven Applications
Understand how Cloud Run supports managed application deployment. Explore request handling, application identity, scaling and event-driven integration using services such as Pub/Sub.
Infrastructure as Code & Delivery Automation
Define and manage Google Cloud resources using Terraform. Examine reusable configurations, state management and deployment workflows, alongside approaches to building and releasing applications with Cloud Build and Artifact Registry.
BigQuery & Data Analytics
Explore how BigQuery supports analytical workloads. Practice working with datasets, querying data and controlling access, while examining how partitioning, clustering and query design can influence performance and cost.
AI & Machine Learning Foundations
Understand the relationship between data preparation, model development, evaluation and application integration. Explore Google Cloud approaches to machine learning and generative AI through demonstrations or focused exercises matched to the audience.
Migration
Assess workload dependencies and migration choices so teams can plan how applications, data and supporting services will be moved to Google Cloud.
Reliability & Cost Management
Examine recovery objectives, availability patterns, observability and cost controls so workloads can be operated, protected and continuously improved.
Practical Google Cloud Workshops
Follow a workload from design to operation.
Hands-on learning connects individual services into working scenarios. Exercises explore why a design is chosen, how components interact and what to check when something fails.
Depending on the agreed program, scenarios may include:
Establish a project foundation
Organize a training environment, enable required services, assign appropriate access and examine the relationship between projects, resources and billing.
Connect and protect a workload
Create a VPC network and subnets, configure firewall controls and investigate connectivity using a defined application scenario.
Deploy a containerized application
Deploy a sample workload to GKE or Cloud Run, examine its access requirements and observe how deployment and scaling choices affect operation.
Build an analytics exercise
Load sample data into BigQuery, run queries and compare approaches to organizing data and managing query costs.
Automate a repeatable environment
Use Terraform to provision selected resources, review proposed changes and explore how teams maintain infrastructure configurations.
Investigate an operational issue
Use logs, metrics and alerts to examine a scenario involving application errors, denied access or connectivity problems.
Role-Based Learning
Different responsibilities need different learning paths.
The starting point depends on the team’s experience. Networking, Linux, containers or SQL knowledge may be relevant to particular tracks.
Teams adopting Google Cloud
Platform foundations, project structure, access and core workflows
Cloud engineers and administrators
Resource deployment, networking, operations and troubleshooting
Architects and technical leads
Service selection, integration, reliability and design trade-offs
Platform and DevOps teams
GKE, Cloud Run, Terraform and delivery automation
Data teams
BigQuery, data access, analytical workflows and query efficiency
Security teams
IAM, service accounts, organization policies and audit visibility
Technology managers
Adoption planning, governance, operating responsibilities and cost awareness
Customized Corporate Programs
Start with the work your team needs to perform.
A useful training plan begins with a practical question: what should participants be able to do after the program?
Your requirements might include establishing a Google Cloud environment, supporting an application migration, operating Kubernetes workloads or helping analysts work effectively with BigQuery.
Training scope is developed around those objectives.
Define the outcomes
Identify the tasks, decisions and responsibilities the program should support.
Review existing skills
Establish prerequisite knowledge and areas that need reinforcement.
Select relevant topics
Combine the platform concepts and technical areas needed by the audience.
Choose practical scenarios
Agree on exercises that connect learning with the intended work.
Deliver and review
Use demonstrations, practice and discussion to reinforce understanding and identify next steps.
Programs can focus on one specialist area or combine related topics into a broader learning journey.
Delivery & Learning Formats
Bring the learning to your team.
Formats include focused workshops, structured corporate programs, bootcamps and technical enablement sessions.
Live Virtual Sessions
Interactive remote instruction with demonstrations, technical discussion and guided practice. Sessions can be organized around the agreed scope and team availability.
Classroom / On-Site Programs
Face-to-face learning that gives teams space to discuss architecture, compare approaches and work through exercises together.
Hybrid Delivery
A coordinated combination of virtual and classroom sessions for distributed teams or programs delivered in stages.
Google Cloud Certification Preparation
Build the reasoning behind the answer.
Certification preparation can be included where it supports your team’s development objectives.
For an architecture-focused program, preparation can explore business requirements, solution design, security, migration choices and operational considerations relevant to the Professional Cloud Architect role.
Learning emphasizes explaining decisions and evaluating alternatives through scenarios and practical exercises. The scope should be aligned with the current exam guide when the program is planned.
Training does not guarantee certification. Exam registration and fees are separate unless expressly included in the engagement.
Architecture Reasoning
Connect business requirements with appropriate Google Cloud design choices.
Scenario Evaluation
Compare alternatives across security, reliability, migration, performance and cost.
Practical Reinforcement
Use technical discussion and exercises to strengthen understanding and decision-making.
Frequently Asked Questions
Google Cloud training, clarified.
Is this page only for Professional Cloud Architect preparation?
No. Training can cover foundations, engineering, networking, GKE, Cloud Run, analytics and operations. Professional Cloud Architect preparation is one possible focus.
Can a team with AWS or Azure experience join?
Yes. A program can build on existing cloud knowledge while explaining Google Cloud concepts such as projects, resource hierarchy, IAM and VPC networking in their own context.
Can we focus on GKE or BigQuery rather than a broad cloud program?
Yes. Specialist workshops can concentrate on a defined topic, with prerequisites and practical exercises selected for the audience.
Will participants work in a practical environment?
Hands-on activities can be included in the agreed scope. Required accounts, permissions, lab access and resource costs should be established before training.
Can you help us understand how Google Cloud connects to on-premises systems?
Yes. Relevant programs can cover hybrid networking concepts, DNS, connectivity choices and the operational considerations involved in connecting environments.
Do we need to share production access?
Training can use a separate lab environment. Any discussion of your existing architecture can use sanitized diagrams and examples appropriate to the engagement.
How is the program duration decided?
Duration follows the learning objectives, participant experience, topic depth and amount of practical work. The schedule is agreed after reviewing these requirements.
Can you train a team spread across locations?
Yes. Virtual and hybrid delivery can support distributed teams, with session arrangements agreed around location and availability.
Plan Your Google Cloud Training
What should your team be able to do next?
Tell me about your current environment, your team’s experience and the responsibilities they are preparing to take on.
Together, we can shape a Google Cloud training program around clear objectives, relevant technical topics and practical application.