Google Cloud Training in Madison, WI

What is Google Cloud

Google Cloud is a suite of cloud computing services offered by Google. It provides a range of tools and services for computing, data storage, data analytics, artificial intelligence, machine learning, and development that allow businesses, organizations, and individuals to build and scale applications efficiently and securely. The platform includes services for storage, networking, databases, AI, and machine learning, among others.

Business Computer Skills offers Google Cloud training classes nationwide and online.

Key Components and Services of Google Cloud

1. Compute
   • Google Compute Engine: Offers virtual machines running in Google�s data centers for tasks like scalable application hosting.
   • Google Kubernetes Engine (GKE): A managed Kubernetes service that provides container orchestration and management.
   • App Engine: A fully managed serverless platform for deploying applications, with support for multiple languages.
2. Storage and Databases
   • Google Cloud Storage: Scalable object storage solution for structured and unstructured data.
   • BigQuery: A fully managed data warehouse that supports SQL and other query languages, designed for handling and analyzing large datasets.
   • Firestore and Firebase: NoSQL databases for mobile, web, and server development with real-time syncing capabilities.
3. Networking
   • Virtual Private Cloud (VPC): Allows users to connect their resources securely with customizable IP ranges.
   • Cloud CDN: Content delivery network that improves website load times and scalability by caching content closer to users.
   • Cloud Interconnect: Connects on-premises resources to Google Cloud through dedicated physical connections.
4. Artificial Intelligence and Machine Learning
   • Cloud AI Platform: Offers tools for building, deploying, and scaling machine learning models.
   • AutoML: Enables users without extensive ML knowledge to train custom models for tasks like image recognition and language processing.
   • Natural Language API and Vision API: Ready-to-use models for NLP and image analysis.
5. Data Analytics
   • BigQuery: For real-time data analysis with high-speed query processing.
   • Dataflow: A fully managed service for stream and batch data processing.
   • Dataproc: Managed Apache Spark and Hadoop service for big data processing.
6. Developer Tools
   • Cloud SDK: Command-line tools for managing Google Cloud resources and deploying applications.
   • Cloud Build: A CI/CD platform that allows developers to automate builds, tests, and deployments.
   • Artifact Registry: A single location for managing container images and other dependencies.
7. Identity and Security
   • Cloud IAM (Identity and Access Management): Provides detailed control over who can access resources within Google Cloud.
   • Cloud Key Management: Manages encryption keys for data security.
   • Security Command Center: Centralizes security insights and provides recommendations to enhance cloud security.
8. Management Tools
   • Operations Suite (formerly Stackdriver): Monitors applications with logging, error reporting, and tracing tools.
   • Cloud Monitoring: Tracks performance and uptime for applications and systems.
   • Cloud Logging: Captures logs from Google Cloud services and other sources.
9. Hybrid and Multi-Cloud Solutions
   • Anthos: A hybrid and multi-cloud platform enabling organizations to run applications consistently across various environments.
   • Cloud Run: Serverless platform for running containers without managing servers.

Benefits of Google Cloud

• Scalability: Google Cloud offers services that allow businesses to scale their infrastructure on-demand.
• Cost-Effectiveness: The platform provides pay-as-you-go pricing, reducing the need for large upfront investments.
• Reliability: Backed by Google�s infrastructure, Google Cloud provides high uptime and disaster recovery capabilities.
• Global Reach: Google Cloud data centers are distributed globally, helping businesses serve users worldwide.
• Enhanced Security: Google invests heavily in security, offering multiple layers of protection, regulatory compliance, and robust identity management.

Use Cases of Google Cloud

• Data Analytics and Business Intelligence: With BigQuery and Data Studio, organizations can gain insights from large datasets quickly.
• Application Development: Developers use App Engine and Cloud Run to build and deploy scalable web and mobile applications.
• Machine Learning and AI: From predictive modeling to image and speech recognition, Google Cloud AI services support various advanced AI applications.
• Hybrid and Multi-Cloud Strategies: Using Anthos, organizations can manage workloads across Google Cloud, on-premises, and other cloud providers.

In summary, Google Cloud is a comprehensive platform designed to support businesses and developers in building, deploying, and scaling applications while providing robust solutions for data management, artificial intelligence, and analytics.

Google Cloud Certifications in 2024

Foundational Level

Google Cloud Digital Leader

• Description: This certification is designed for individuals who want to establish a foundational understanding of Google Cloud�s core services. It covers general knowledge of cloud computing concepts and helps individuals understand Google Cloud�s products and services, especially relevant to non-technical roles such as sales, marketing, and management.
• Ideal for: Individuals starting with Google Cloud who need foundational knowledge, regardless of a technical background.

Associate Level

Google Cloud Associate Cloud Engineer

• Description: This certification validates the ability to deploy, monitor, and maintain projects on Google Cloud. It focuses on essential Google Cloud tasks, such as setting up a cloud environment, managing cloud storage, and configuring network settings. It is a step up from the foundational level, requiring hands-on familiarity with Google Cloud tools.
• Ideal for: Entry-level cloud engineers or IT professionals who are managing Google Cloud-based solutions.

Professional Level

Google Cloud Professional Data Engineer

• Description: This certification assesses skills in designing, building, and operationalizing data processing systems. It focuses on data engineering concepts, including machine learning models, data analysis, and the creation of scalable and reliable data pipelines on Google Cloud.
• Ideal for: Data engineers and professionals involved in data analytics and data science with hands-on Google Cloud experience.

Google Cloud Professional Cloud Architect

• Description: The certification evaluates an individual's ability to design and plan cloud solution architecture, manage the cloud infrastructure, and ensure reliability and scalability. It also covers security and compliance, making it one of the more comprehensive certifications.
• Ideal for: Cloud architects and engineers who need to design highly available, secure, and scalable solutions on Google Cloud.

Google Cloud Professional Cloud Developer

• Description: This certification targets developers who build applications on Google Cloud. It focuses on cloud-native development, including cloud services, API integrations, and using Google Kubernetes Engine. This certification requires strong coding and cloud-native development skills.
• Ideal for: Developers and software engineers focusing on building and deploying cloud applications.

Google Cloud Professional Cloud Security Engineer

• Description: This certification focuses on security practices for Google Cloud, including configuring access control, defining security policies, and using Google security services like IAM, VPC Service Controls, and encryption. It�s a specialized certification aimed at security professionals.
• Ideal for: Security engineers and professionals who are responsible for maintaining secure Google Cloud environments.

Google Cloud Professional Machine Learning Engineer

• Description: This certification is designed for individuals who want to create and deploy machine learning models on Google Cloud. It covers both machine learning techniques and Google�s tools like TensorFlow and BigQuery ML, essential for building scalable ML solutions.
• Ideal for: Machine learning engineers and data scientists with experience in Google Cloud�s machine learning tools and frameworks.

Google Cloud Professional Cloud Network Engineer

• Description: This certification evaluates knowledge of implementing and managing network architectures on Google Cloud. It covers network design, hybrid networking, and managing network security, specifically focusing on the Google Cloud environment.
• Ideal for: Network engineers or IT professionals specializing in network design and implementation within the Google Cloud ecosystem.

Google Cloud Professional Collaboration Engineer

• Description: This certification targets individuals managing Google Workspace solutions. It focuses on managing users, applications, and security for Google Workspace, as well as optimizing collaboration within organizations.
• Ideal for: IT administrators and collaboration engineers who are responsible for deploying and managing Google Workspace for organizations.

Jobs That Use Google Cloud

1. Cloud Engineer

Roles: Cloud Engineers focus on setting up, managing, and maintaining Google Cloud environments. They work with virtual machines, networks, and storage to support company operations on the cloud.

Responsibilities:

• Implement and manage cloud resources using Google Cloud tools.
• Monitor and optimize cloud infrastructure for performance and cost-effectiveness.
• Ensure security and compliance of cloud systems.

2. Data Engineer

Roles: Data Engineers use Google Cloud to build and manage data pipelines, ensuring data is available, reliable, and usable for analytics and business intelligence.

Responsibilities:

• Create, maintain, and optimize data pipelines on Google Cloud.
• Design data models for efficient storage and retrieval.
• Work closely with data scientists and analysts to ensure data accessibility and quality.

3. Solutions Architect

Roles: Solutions Architects design and plan cloud solutions tailored to meet business requirements. They bridge the gap between technical teams and business stakeholders.

Responsibilities:

• Analyze business requirements to develop Google Cloud-based solutions.
• Create architecture diagrams and documentation for proposed solutions.
• Collaborate with engineering teams to implement and deploy cloud solutions.

4. Cloud Security Engineer

Roles: Cloud Security Engineers focus on ensuring the security of cloud environments, protecting data, and implementing best practices in cloud security.

Responsibilities:

• Develop and enforce security policies and access controls.
• Monitor for security threats and vulnerabilities within Google Cloud environments.
• Implement security measures like encryption, network firewalls, and identity management.

5. DevOps Engineer

Roles: DevOps Engineers leverage Google Cloud to automate deployment processes, manage continuous integration/continuous deployment (CI/CD) pipelines, and improve cloud-based workflows.

Responsibilities:

• Build and manage CI/CD pipelines on Google Cloud.
• Automate infrastructure provisioning and application deployment.
• Optimize cloud processes to improve efficiency and reliability.

6. Machine Learning Engineer

Roles: Machine Learning Engineers use Google Cloud�s AI and machine learning services to build, train, and deploy models for predictive analytics and other applications.

Responsibilities:

• Design and implement machine learning models on Google Cloud.
• Utilize tools like TensorFlow and AutoML for model development and training.
• Deploy models to production and monitor their performance over time.

We offer live-instructor group training classes for your team.

Upskill your team from the comfort of your office or online.

Benefits of Group Training Include:

• Experienced Professional Instructor Trains Your Team
• Content Focused On Your Team's Needs
• Convenient Scheduling and Class Setup
• Significant Per/Student Cost Savings
• Online, On-Site and Blended Options Available

Get A Free Consultation

Madison is an interesting place. Here is some information to help you learn more about Madison

Below is a list of local libraries in the area that may also provide computer training near Madison, Wisconsin:

We offer live-instructor group training classes for your team.

Upskill your team from the comfort of your office or online.

Benefits of Group Training Include:

• Experienced Professional Instructor Trains Your Team
• Content Focused On Your Team's Needs
• Convenient Scheduling and Class Setup
• Significant Per/Student Cost Savings
• Online, On-Site and Blended Options Available

Get A Free Consultation