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Cloud Digital Leader Cloud Digital Leader lessons
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A week-by-week plan with every lesson, quizzes, checkpoint tests, a practice exam and hands-on labs.
Open the Cloud Digital Leader study planA week-by-week plan with every lesson, quizzes, checkpoint tests, a practice exam and hands-on labs.
Domain 1: Digital transformation with Google Cloud
- What cloud computing is and why it drives digital transformation
- Business benefits of the cloud: scalability, elasticity, agility, reliability and strategic value
- CapEx vs OpEx and total cost of ownership (TCO) when moving to the cloud
- Deployment options: on-premises, private cloud, public cloud, hybrid cloud and multicloud
- Cloud service models: IaaS, PaaS, SaaS and serverless, and what the customer manages in each
- The shared responsibility model and how it changes with the service model
- Google Cloud global infrastructure: regions, zones, edge points of presence and Google's private network
- Network performance basics: bandwidth, latency and choosing locations close to users
- Open source, open standards and avoiding vendor lock-in
- Leading digital transformation: culture, skills and change management in a cloud adoption
Domain 2: Exploring data transformation with Google Cloud
- Why data matters: using data to drive decisions, products and innovation
- Structured, semi-structured and unstructured data
- Databases, data warehouses and data lakes: what each is for
- Cloud Storage and its storage classes: Standard, Nearline, Coldline and Archive
- Relational databases on Google Cloud: Cloud SQL, AlloyDB and Spanner
- Non-relational databases on Google Cloud: Firestore and Bigtable
- BigQuery: serverless data warehouse and analytics
- Streaming and processing data: Pub/Sub, Dataflow and Dataproc
- Business intelligence with Looker and Looker Studio
- Moving data to Google Cloud: Database Migration Service, BigQuery Data Transfer Service, Storage Transfer Service and Transfer Appliance
- Data governance: quality, security, access control and cataloging
Domain 3: Innovating with Google Cloud artificial intelligence
- Artificial intelligence, machine learning and generative AI: definitions and differences
- Business problems machine learning can solve, and when ML is not the right tool
- Data quality for machine learning: accuracy, completeness, representativeness and bias
- Responsible AI: Google's AI Principles, fairness, explainability, privacy and accountability
- Pre-trained AI APIs: Vision, Natural Language, Speech-to-Text, Text-to-Speech and Translation
- BigQuery ML: building and using models with SQL where the data already lives
- Vertex AI: the unified ML platform, AutoML and custom training
- Choosing an AI approach: pre-trained API, BigQuery ML, AutoML or custom model
- Generative AI on Google Cloud: Gemini models, Vertex AI Model Garden and Vertex AI Studio
- Grounding, agents and AI-powered search and conversation for business
- AI infrastructure: GPUs and Tensor Processing Units (TPUs)
Domain 4: Modernize infrastructure and applications with Google Cloud
- Why modernize: benefits of moving infrastructure and applications to the cloud
- Migration approaches: retire, retain, rehost (lift and shift), replatform, refactor and reimagine
- Virtual machines with Compute Engine: machine types, managed instance groups and autoscaling
- Keeping existing platforms: Google Cloud VMware Engine and Bare Metal Solution
- Containers: what they are and why they make applications portable
- Google Kubernetes Engine (GKE): managed Kubernetes in Standard and Autopilot modes
- Serverless computing: Cloud Run, Cloud Run functions and App Engine
- Choosing compute for a workload: VMs vs containers vs serverless
- Monoliths vs microservices and application modernization
- APIs and API management with Apigee
- Hybrid and multicloud with GKE Enterprise (formerly Anthos)
Domain 5: Trust and security with Google Cloud
- Core security concepts: confidentiality, integrity, availability, privacy, control and compliance
- Cloud security vs on-premises security, and shared responsibility for security
- Common cloud threats: misconfiguration, compromised credentials, phishing, malware and ransomware
- Zero trust and defense in depth
- Google's secure infrastructure: data centers, custom hardware, Titan chips and the private network
- Encryption at rest and in transit, and key management with Cloud KMS
- Identity and access management: principals, roles, least privilege and two-step verification
- Network and perimeter security: firewall rules, Cloud Armor and VPC Service Controls
- Security operations: Security Command Center, audit logs and Google Security Operations
- Data residency, data sovereignty and Assured Workloads
- Compliance and transparency: compliance reports, Access Transparency and Google's trust principles
Domain 6: Scaling with Google Cloud operations
- Cloud financial governance and FinOps: shared accountability for cloud cost
- The Google Cloud resource hierarchy: organization, folders, projects and resources
- Policy inheritance: IAM allow policies and organization policies through the hierarchy
- Controlling costs: billing accounts, budgets and alerts, quotas, labels and billing export
- Pricing models and discounts: pay-as-you-go, sustained use discounts, committed use discounts and Spot VMs
- DevOps and Site Reliability Engineering (SRE) principles
- SLIs, SLOs, SLAs and error budgets
- Reliability and disaster recovery: redundancy across zones and regions, backups, RTO and RPO
- Google Cloud Observability: Cloud Monitoring, Cloud Logging, Cloud Trace and Error Reporting
- Google Cloud Customer Care: support plans and when to use them
- Sustainability: Google's carbon-free energy goals, low-carbon regions and the Carbon Footprint tool