Google Cloud Computing Foundations Course & Certification Online

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Course Highlights

Provides an overview of Cloud Basics, Big Data, and Machine Learning, and introduces Google Cloud tools.
Enables learners to develop technical proficiency and pivot to careers in a cloud‑first world.
Consists of four courses that include hands‑on labs to practise key skills and produce work examples.
Learners can earn four Skill Badges to demonstrate proficiency with Google Cloud products and services.
The programme takes approximately 40-50 hours to complete.

Upon completion of the programme, learners will be able to:

Discuss Cloud Computing and identify its advantages, and compare physical, virtual, and cloud architectures.
Implement a variety of structured and unstructured storage models in the cloud.
Describe the shared security model, Google’s and the customer’s security responsibilities, and best practices for authentication and authorisation.
Build Virtual Private Clouds (VPCs) and explore hybrid‑cloud networking options and load balancing.
Describe the use of managed big data services such as Dataproc and BigQuery.
Introduce Machine Learning and build custom models using Vertex AI and AutoML, and apply pre‑trained models using Google’s machine‑learning APIs.

Provides foundational knowledge and skills in cloud-based computing for those with little to no experience.
Enables you to develop technical proficiency and launch or pivot to a career in a cloud-first world.
Includes hands-on labs to practise key skills and produce work examples for employers.
Allows you to earn four Skill Badges from Google Cloud to prove your proficiency in an interactive, hands-on environment.
Only for higher‑education students; 18+ years is mandatory. A college degree is not a prerequisite.

Individuals with little to no background or experience in Cloud Computing.
Learners who want to understand Cloud Basics, Big Data, Machine Learning, and how Google Cloud fits in.
Individuals who have basic IT knowledge and are interested in learning more about Cloud Computing and Machine Learning.
Those with a basic understanding of shell scripting and SQL, and competency in at least one computer language (helpful, though not required).

The programme includes four courses:

Course 1: Google Cloud Computing Foundations: Cloud Computing Fundamentals (approx. six hours): Introduces Cloud Computing, its advantages, IaaS, PaaS, and SaaS, and explores Google Cloud Console, projects, APIs, and compute options such as Virtual Machines and Cloud Functions.
Course 2: Google Cloud Computing Foundations: Infrastructure in Google Cloud (approx. five hours): Covers cloud storage (structured/unstructured, relational/NoSQL), APIs, the shared security model, encryption, authentication, and authorisation.
Course 3: Google Cloud Computing Foundations: Networking and Security in Google Cloud (approx. five hours): Focuses on networking, including virtual private clouds (VPCs), firewall rules, load balancing, hybrid‑cloud networking, and cloud automation/management tools such as Cloud Deployment Manager, monitoring, and logging.
Course 4: Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud (approx. seven hours): Introduces big data managed services such as Dataproc and BigQuery, and machine‑learning concepts, including building models with Vertex AI and AutoML, and using pre‑trained ML APIs.

4 skill badges :

Skill Badge 1: Implement Load Balancing on Compute Engine: Complete the introductory Implement Load Balancing on Compute Engine skill badge to demonstrate skills in the following: writing gcloud commands and using Cloud Shell, creating and deploying virtual machines in Compute Engine, and configuring network and HTTP load balancers.
Skill Badge 2: Set Up an App Dev Environment on Google Cloud: Earn a skill badge* by completing the Set Up an App Dev Environment on Google Cloud course, where you learn how to build and connect storage‑centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
Skill Badge 3: Build a Secure Google Cloud Network: Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you learn about multiple networking‑related resources to build, scale, and secure your applications on Google Cloud.
Skill Badge 4: Prepare Data for ML APIs on Google Cloud: Complete the Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech‑to‑Text API, and the Video Intelligence API.

Skills:

Identifying the advantages of the cloud and defining IaaS, PaaS, and SaaS
Building and managing virtual machines, and elastic applications using autoscaling
Implementing structured and unstructured cloud storage models
Building secure networks, including VPCs, firewall rules, and hybrid cloud networking
Load balancing, monitoring, logging, tracing, debugging, and error reporting in the cloud
Using Dataproc, BigQuery, Vertex AI, AutoML, and Machine Learning APIs

Tools:

Google Cloud Console and Cloud Shell
Google Cloud Projects
Compute Engine (virtual machines, load balancers)
Cloud Functions
Cloud Storage
Cloud IAM
Pub/Sub
Cloud Deployment Manager
Dataproc
BigQuery
Vertex AI and AutoML
Cloud Natural Language API, Google Cloud Speech-to-Text API, Video Intelligence API