- Explain why cloud technology is transforming business, including cloud versus on-premises, public/private/hybrid/multicloud, and Google Cloud’s transformation benefits.
- Apply fundamental cloud concepts: flexibility, scalability, reliability, elasticity, agility, TCO, and the shift from CapEx to OpEx.
- Describe basic network infrastructure terms and how Google’s global infrastructure supports digital transformation.
- Compare IaaS, PaaS, and SaaS trade-offs and the cloud shared responsibility model for different business scenarios.
Google Cloud Digital Leader exam preparation
Google Cloud Digital Leader Certification Training Course
Accumentum’s Cloud Digital Leader training prepares professionals to articulate Google Cloud capabilities, common business use cases, and how cloud solutions support an enterprise, without requiring a deep engineering background.
Course focus: Digital transformation, data, AI, infrastructure and application modernization, trust and security, and cloud operations, mapped to the official Cloud Digital Leader exam guide.
Course Overview
The Google Cloud Digital Leader Certification Training Course with Accumentum is for anyone who wants to demonstrate knowledge of cloud.
The Google Cloud Digital Leader Certification Training Course with Accumentum is for anyone who wants to demonstrate knowledge of cloud computing basics and how Google Cloud products and services help an organization reach its goals. A Cloud Digital Leader can articulate the capabilities of Google Cloud core products and services and describe common business use cases. The course follows the official exam guide: digital transformation with Google Cloud, exploring data transformation. Innovating with Google Cloud artificial intelligence. Modernizing infrastructure and applications, trust and security. And scaling with Google Cloud operations. Accumentum keeps the emphasis on conceptual fluency and business value, not low-level engineering tasks.
Course Objectives
Course objectives for the Google Cloud Digital Leader Certification Training Course.
01
Frame digital transformation
Explain why cloud technology transforms business, fundamental cloud concepts, IaaS/PaaS/SaaS trade-offs, and the shared responsibility model.
02
Connect data and AI to value
Describe data management options, analytics and streaming, and when pre-trained APIs, AutoML, or custom Vertex AI models fit a use case.
03
Modernize with trust
Discuss compute, serverless, containers, APIs, hybrid and multicloud, plus Google’s trust principles, encryption, IAM, and compliance resources.
04
Operate and govern cloud spend
Describe financial governance, reliability at scale, customer care, and how Google Cloud supports sustainability goals.
Who Should Attend
- Business and product leaders: Managers who need cloud fluency to sponsor transformation, data, and AI initiatives.
- Sales, customer success, and consulting roles: Professionals who must explain Google Cloud capabilities and use cases to stakeholders.
- Career changers and cloud newcomers: Learners who want a business-level Google Cloud credential before deeper engineering certifications.
- Finance, operations, and program staff: People who work with cloud cost, governance, or delivery and need a shared vocabulary with technical teams.
Prerequisites
- No engineering prerequisite: The Cloud Digital Leader exam is designed for a broad audience. You do not need to design production architectures to start.
- Business context helps: Familiarity with how your organization uses technology, data, or vendors makes the scenarios easier to absorb.
- Willingness to learn product families: You should be ready to distinguish core Google Cloud products at a conceptual level (what they are for, not how to configure every flag).
- Exam commitment: Motivation to work through all six official exam-guide sections. The weights are nearly even, so skipping a domain is a poor plan.
Pathway Map
6 modules covering the Digital Leader exam domains.
Course modules: Digital Transformation with Google Cloud, Exploring Data Transformation with Google Cloud, Innovating with Google Cloud Artificial Intelligence, Modernize Infrastructure and Applications with Google Cloud, Trust and Security with Google Clo.
Course Content
- Describe the role of data in digital transformation, including databases, warehouses, lakes, structured and unstructured data, and data governance.
- Match Google Cloud data products to use cases: Cloud Storage, Cloud SQL, Spanner, Bigtable, BigQuery, and Firestore.
- Differentiate Cloud Storage classes and options for migrating or modernizing databases.
- Explain how Looker, streaming analytics, Pub/Sub, and Dataflow make data useful and accessible.
- Define AI and ML, the problems ML can solve, and why high-quality data and responsible, explainable AI matter.
- Select among pre-trained APIs, AutoML, and custom models based on speed, effort, differentiation, and required expertise.
- Describe BigQuery ML, pre-trained APIs (Vision, Translation, Speech, Natural Language), AutoML, Vertex AI, TensorFlow, and Cloud TPU at a conceptual level.
- Practice recommending an AI path that fits a business use case rather than a product checklist.
- Explain migration terms: retire, retain, rehost, replatform, refactor, and reimagine, and why each application may take a different path.
- Discuss compute options: VMs, containers, microservices, serverless, preemptible VMs, Kubernetes, autoscaling, and load balancing.
- Describe the business value of Compute Engine, Cloud Run, App Engine, Cloud Functions, GKE, Apigee, and Anthos for hybrid or multicloud.
- Connect modernization choices to cost, staffing, and operational responsibility.
- Discuss fundamental cloud security concepts and how they differ from traditional on-premises security.
- Explain Google’s defense-in-depth infrastructure, encryption, authentication/authorization/auditing, 2SV, IAM, Cloud Armor, and SecOps.
- Describe Google Cloud trust principles, transparency reports, third-party audits, data sovereignty and residency, and the compliance resource center.
- Apply shared responsibility thinking to control, compliance, confidentiality, integrity, and availability.
- Discuss financial governance: resource hierarchy, quotas, budgets, and Cloud Billing reports for predictable cloud consumption.
- Describe modern operations, reliability, resilience, high availability, disaster recovery, DevOps, and SRE terms at a business level.
- Explain how Google Cloud Customer Care supports cloud adoption and the life of a support case.
- Describe how Google Cloud helps organizations meet sustainability goals and reduce environmental impact.
Course Features
Interactive Digital Leader exam preparation with Accumentum.
Interactive Learning
Practice explaining Google Cloud capabilities in business language through discussion and scenario prompts.
Comprehensive Study Materials
Structured coverage of all six official exam-guide sections, including data, AI, security, and operations.
Real-World Applications
Map IaaS/PaaS/SaaS, migration paths, and AI options to situations leaders actually sponsor.
Certification Preparation
Guidance for the Cloud Digital Leader exam focused on conceptual fluency, not deep configuration.
Certification Exam
Prepare for the official Google Cloud Digital Leader exam.
Digital Leader Exam Readiness
Accumentum Digital Leader training prepares learners for the Google Cloud Digital Leader certification exam.
Upon completing the Google Cloud Digital Leader Certification Training Course with Accumentum, you will be prepared to take the official Cloud Digital Leader exam. The credential shows you can articulate Google Cloud core products and services and how they support enterprise goals. Accumentum does not invent exam prices or passing scores. Confirm current exam logistics on Google’s certification site when you schedule.
Exam Blueprint
What Google says the CDL exam covers.
Google's Cloud Digital Leader exam guide has 6 sections and 14 objectives. We've copied each one below in Google's own wording, with the approximate share of the exam it carries.
Google describes the role this way: "This exam guide outlines the topics that may appear on both the standard and renewal exams. A Cloud Digital Leader can articulate the capabilities of Google Cloud core products and services and how they benefit organizations. They can also describe common business use cases and how cloud solutions support an enterprise. This certification is for anyone who wants to demonstrate their knowledge of cloud computing basics and how Google Cloud products and services can be used to achieve an organization’s goals."
Section 1: Digital Transformation with Google Cloud (about 18% of the exam)
1.1 Explain why and how the cloud is revolutionizing businesses
- Define the terms: cloud, agentic AI, infrastructure, digital transformation, open source, open standard.
- Explain the benefits of cloud technology to a business’ digital transformation (for example scalability, cost-effectiveness, agility, speed, flexibility, enhanced security, global reach and high availability, data-driven insights, strategic value and focus).
- Describe the primary drivers that compel organizations to pursue digital transformation and the significant challenges they face (that is factors that motivate organizations to transform, common hurdles that can affect transformation, implications and risks of not adopting cloud).
- Recognize some of Google Cloud’s top differentiators (for example world-leading AI, deep commitment to openness and interoperability, AI Hypercomputer, AI-ready data platform, security, global network).
1.2 Describe fundamental cloud concepts
- Identify the corresponding business use case and benefits of various cloud architectures (for example private cloud, hybrid cloud, multicloud).
- Define fundamental networking concepts and describe how Google Cloud’s global network infrastructure supports digital transformation (for example IP address, domain name service (DNS), basic IP addresses, latency, bandwidth).
- Describe the components of Google Cloud’s network and explain how they work together (for example regions, zones, edge locations).
- Describe the benefits and tradeoffs of different cloud service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)
Section 2: Exploring Data Transformation with Google Cloud (about 18% of the exam)
2.1 Describe the intrinsic role that data plays in an organization’s digital transformation
- Explain why data is valuable (for example generating real-time business insights, identifying trends, informing strategic decision making, fueling AI).
- Differentiate between databases, data warehouses, and data lakes.
- Recognize types of data (for example first-party, second-party, third-party, structured, unstructured, semi-structured).
- Describe an organization’s data supply chain (for example data genesis, data collection, data processing, data storage, data analysis, data activation).
- Describe the data governance process and why it’s important.
- Explain why openness and interoperability with data management platforms are critical for eliminating data silos and avoiding vendor lock-in.
2.2 Determine which Google Cloud data management products are applicable to different business use cases
- Determine which Google Cloud data management offering is best for each business use case (for example Cloud Storage, Spanner, Cloud SQL, AlloyDB, Bigtable, BigQuery, Firestore).
- Define key data management concepts and terms (for example relational, non-relational, object storage, structured query language [SQL], NoSQL).
- Differentiate between storage classes in Cloud Storage regarding cost and frequency of access (for example Standard, Nearline, Coldline, Archive, Autoclass).
- Describe the ways that an organization can migrate or modernize their current database in the cloud.
2.3 Discuss how smart analytics, business intelligence tools, and streaming analytics can add value in different business use cases
- Describe how Looker democratizes access to data.
- Recognize the value of analyzing and visualizing data from BigQuery in Looker to create real-time reports, dashboards, and integrating data into workflows.
- Explain why real-time streaming analytics is critical for modern businesses.
- Describe the main Google Cloud products that modernize data pipelines (for example Pub/Sub, Dataflow, Managed Service for Apache Spark).
Section 3: Innovating with Google Cloud Artificial Intelligence (about 18% of the exam)
3.1 Describe fundamental AI and ML concepts and how they create business value
- Recognize the definition of artificial intelligence (AI), machine learning (ML), generative AI (gen AI), data analytics, and business intelligence.
- Recognize some of the ways agentic AI is fundamentally reshaping different industries and the way people work (for example workforce productivity, customer support, sales experiences, product innovation, operations, research).
- Recognize the key benefits of Google Cloud’s AI offerings (for example best infrastructure for AI, AI-ready data cloud, sophisticated 1P models, all-in-one AI developer platform, pre-built AI agents and applications).
- Identify the business problems that ML can solve, and describe key use cases and the business value that ML provides (for example replacing or simplifying rule-based systems, deriving business insights from large datasets [structured and unstructured], scaling business decisions).
- Explain why high-quality, accurate data is essential for successful AI models and identify the main dimensions of data quality (for example completeness, uniqueness, timeliness, validity, accuracy, consistency).
- Describe the business implications of explainable and responsible AI in AI systems.
3.2 Explain how Google Cloud’s AI offerings can create business value
- Describe the strategic considerations that organizations must make when selecting Google Cloud AI solutions (for example implementation speed, development effort, potential for business differentiation, technical expertise requirements, choice and flexibility).
- Describe the functionality of Gemini Enterprise Agent Platform and identify potential business use cases.
- Match the Google Cloud pre-trained API and foundation model to various business use cases (for example Agent Platform API, Vision API, Cloud Translation API, Speech-to-Text API, Gemini).
- Explain how an organization can build custom models using their own data to create business value (for example Agent Studio on Agent Platform, AutoML on Agent Platform).
- Recognize the core components of Google Cloud’s AI Hypercomputer and how organizations benefit by gaining improved performance and efficiency for AI workloads (for example GPUs and TPUs, industry-leading software and open standards, cost control with flexible consumption models).
- Discuss how BigQuery ML lets users create and execute machine learning models in BigQuery by using standard SQL queries and flexibility to experiment with data.
Section 4: Modernize Infrastructure and Applications with Google Cloud (about 18% of the exam)
4.1 Describe how Google Cloud helps organizations transition to the cloud
- Define fundamental cloud migration terms (for example workload, discovery and assessment, retire, retain, rehost [lift and shift], replatform [move and improve], refactor, reimagine).
- Define the fundamental cloud compute terms (for example virtual machines (VMs), containerization and containers, applications and microservices, serverless computing, spot VMs, Kubernetes, autoscaling and load balancing, managed services).
4.2 Describe the functionality, business use cases, and business value of Google Cloud’s infrastructure offerings
- Discuss the business value of using Compute Engine to create and run virtual machines on Google’s infrastructure.
- Describe the business value of modern application development (for example flexible architectures like microservices, accelerated deployment processes through managed services, cost optimization, enhanced scalability and resilience, improved operational efficiency).
- Describe the business value of using GKE to deploy and manage containers.
- Describe the business value of using serverless computing Google Cloud products (for example Cloud Run, Cloud Run functions).
- Recognize the Google Cloud products that are supported on multicloud and hybrid cloud environments (for example AlloyDB Omni, BigQuery Omni, GKE Enterprise, Cloud SQL, Looker).
4.3 Describe the business value of application programming interfaces (APIs)
- Define application programming interface (API).
- Describe how organizations can create new business opportunities by exposing and monetizing public-facing APIs.
- Describe the business value of using Apigee API Management.
Section 5: Trust and Security with Google Cloud (about 18% of the exam)
5.1 Describe fundamental cloud security concepts
- Describe relevant cybersecurity threats and business implications (for example DDoS, ransomware, cryptomining, malware, viruses, phishing, misconfiguration, unsecured third party systems, physical damage, LLM attacks).
- Differentiate between cloud security and on-premises security.
- Describe the importance of control, compliance, confidentiality, integrity, and availability in a cloud security model.
- Define key security terms and concepts (for example data loss prevention, privileged access, least privilege, zero-trust architecture, security by default, security posture, cyber resilience, firewall, encryption, decryption).
- Explain how encryption safeguards an organization’s data in different usage states (for example in use, in transit, at rest).
- Differentiate between authentication, authorization, and auditing (for example multi-factor authentication, two-step verification [2SV], IAM).
- Define the fundamental cloud security operations (SecOps) terms (for example security posture, threat intelligence, threat response).
5.2 Describe the business value of making Google part of an organization’s security team with its defense-in-depth, multilayered approach to cloud security
- Recognize how Google Cloud secures every layer of the AI stack (for example infrastructure, data, models, platform, agents).
- Recognize how Google Threat Intelligence provides organizations with proactive insights into cyber threats and identify the unique sources that power its analysis (for example Google’s vast global visibility, Mandiant’s frontline incident response expertise, VirusTotal’s crowd sourced threat detection).
- Recognize the benefits of Security Command Center to proactively discover, prioritize, and remediate security risks and misconfigurations across the Google Cloud environment.
- Recognize the benefits of using a unified security operations platform, like Google Security Operations, to ingest telemetry and accelerate threat detection and response.
- Recognize the benefits of Google’s secure-by-design cloud platform (for example core infrastructure, proprietary data centers, purpose-built servers and networking, custom security hardware and software).
- Recognize the functionality, business value, and use cases for Google Cloud’s AI-assisted and AI-focused security offerings (for example Gemini in Google Security Operations, AI Protection, Model Armor).
- Recognize the functionality, use cases, and business value of Google’s other security offerings (for example Cloud VPC, Cloud VPN, Cloud Interconnect, firewalls, Cloud Armor, Cloud Logging, IAM, Sensitive Data Protection, Confidential Computing, Certificate Manager, Identity-Aware Proxy).
- Describe how Google Cloud earns and maintains customer trust in the cloud (for example transparency reports, third-party audits, digital sovereignty, data residency, compliance resource manager).
Section 6: Scaling with Google Cloud Operations (about 10% of the exam)
6.1 Recognize how Google Cloud supports an organization’s ability to control their cloud costs
- Explain how an organization’s transition from an on-premises environment to the cloud shifts their capital expenditures (CapEx) to operational expenditures (OpEx), and how that affects their total cost of ownership (TCO).
- Describe Google-recommended practices for cloud financial governance (for example identify who manages cloud costs, Google Cloud’s cost management tools).
- Recognize the role of people, process, and technology in controlling cloud costs.
- Recognize the components of Google Cloud’s resource hierarchy (for example resources, projects, folders, organization node) and the benefits (for example access control, inheritance and propagation rules, security and compliance, visibility and auditing capabilities).
- Recognize how to control cloud consumption (for example resource quota policies, budget threshold rules, Cloud Billing reports, Dynamic Workload Scheduler, Spot VMs).
6.2 Describe the fundamental concepts of modern operations, reliability, and resilience in the cloud
- Describe how to modernize operations by using Google Cloud’s Observability (for example operations suite, Cloud Monitoring, Cloud Logging, Cloud Trace, Cloud Profiler, Error Reporting).
- Recognize the fundamental cloud operations terms (for example operational excellence, reliability, high availability).
- Recognize how to design resilient infrastructure and processes (for example redundancy, replication, scalable infrastructure, backups).
- Recognize how a system’s performance and reliability are measured (for example latency, traffic, saturation, errors).
- Recognize fundamental concepts of DevOps and Site Reliability Engineering (for example service level indicators, service level objectives, service level agreements).
Who It Is For
Is CDL the right fit for you?
Google says this certification is for anyone who wants to demonstrate their knowledge of cloud computing basics and how Google Cloud products and services can be used to achieve an organization's goals. In our classes that means product managers, sales and account teams, business analysts, project leads and executives, plus technical staff who are new to Google Cloud.
Google lists no prerequisites. Its recommended experience is experience collaborating with technical professionals.
Exam Format
How the CDL exam works.
Exam details
- Length: 90 minutes
- Registration fee: $99 (plus tax where applicable)
- Languages: English, Japanese, Spanish, Portuguese and French
- Format: 50 to 60 multiple choice and multiple select questions
- Delivery: online proctored from a remote location, or onsite at a testing center
- Prerequisites: none
- Validity period: 3 years
Google doesn't publish a passing score on the certification page, so we don't guess at one. What we can tell you is how the questions behave. Multiple select items ask for more than one correct answer. In our experience, many questions are short scenarios where two options look reasonable and only one fits every requirement in the prompt.
That's why we train you to read for the constraint first. Cost, latency, compliance, operational effort and time to deliver are the words that usually decide the answer.
Study Plan
A practical path to CDL.
We start with Section 1, Digital Transformation with Google Cloud. It's about 18% of the exam, so we work its 2 objectives in hands-on labs and short scenario drills.
Next we cover Section 2, Exploring Data Transformation with Google Cloud. It's about 18% of the exam, so we work its 3 objectives in hands-on labs and short scenario drills.
Then we move to Section 3, Innovating with Google Cloud Artificial Intelligence. It's about 18% of the exam, so we work its 2 objectives in hands-on labs and short scenario drills.
After that comes Section 4, Modernize Infrastructure and Applications with Google Cloud. It's about 18% of the exam, so we work its 3 objectives in hands-on labs and short scenario drills.
We follow with Section 5, Trust and Security with Google Cloud. It's about 18% of the exam, so we work its 2 objectives in hands-on labs and short scenario drills.
We wrap up with Section 6, Scaling with Google Cloud Operations. It's about 10% of the exam, so we work its 2 objectives in hands-on labs and short scenario drills.
Section 1 carries the most weight, so it gets the most review time. In the last week we run timed practice at the real pace, revisit your weakest sections and reread the exam guide line by line. Google also publishes sample questions and a learning path on the certification page, and we use both.
Exam Policies
Retakes and renewal for CDL.
Google's retake policy for foundational exams allows a maximum of ten attempts within a one year period, with at least 14 days between each failed attempt.
Every attempt counts toward that limit, whatever the language or delivery method, and payment is required each time you register.
Foundational and associate certifications can be renewed starting 180 days before the expiration date. Google lets you renew by taking the standard exam, a shorter renewal exam or completing designated courses or skill badges in Google Skills.
Online proctored exams run through Pearson. Google notes that if a session can't be restarted after you've seen exam content, the attempt counts and the retake policy applies, so check your system and connection ahead of time.
Career Outlook
Where CDL can take you.
CDL is aimed at business and technical staff who work alongside cloud teams. BLS doesn't track cloud roles separately, so we use the closest occupation as a reference.
Per the U.S. Bureau of Labor Statistics, computer and information systems managers earned a median annual wage of $175,140 in May 2025. Treat it as a reference point and not a promise. Location, experience and the employer drive what any one person earns. Source: BLS Occupational Outlook Handbook.
Funding
Ways to pay for CDL training.
Paying on your own? CDL prep is eligible for PathPay, our monthly payment plan. Terms of 3, 4 and 6 months carry no added fee. 9, 12 and 18 month terms add 5%, 10% and 15%. Course access opens when your first payment clears.
Our funding page lists every other way to pay, and you can always talk with us or email info@accumentum.net before you enroll.
Frequently Asked Questions
Digital Leader with Accumentum: audience, prerequisites, course content, exam, and enrollment.
The Google Cloud Digital Leader Certification Training Course with Accumentum is for anyone who wants to demonstrate knowledge of cloud computing basics and how Google Cloud products and services help an organization reach its goals. Digital transformation, data, AI, infrastructure and application modernization, trust and security, and cloud operations, mapped to the official Cloud Digital Leader exam guide.
Business and product leaders: Managers who need cloud fluency to sponsor transformation, data, and AI initiatives. Sales, customer success, and consulting roles: Professionals who must explain Google Cloud capabilities and use cases to stakeholders. Career changers and cloud newcomers: Learners who want a business-level Google Cloud credential before deeper engineering certifications. Finance, operations, and program staff: People who work with cloud cost, governance, or delivery and need a shared vocabulary with technical teams.
No engineering prerequisite: The Cloud Digital Leader exam is designed for a broad audience. You do not need to design production architectures to start. Business context helps: Familiarity with how your organization uses technology, data, or vendors makes the scenarios easier to absorb. Willingness to learn product families: You should be ready to distinguish core Google Cloud products at a conceptual level (what they are for, not how to configure every flag). Exam commitment: Motivation to work through all six official exam-guide sections. The weights are nearly even, so skipping a domain is a poor plan.
6 course-content areas: Digital Transformation with Google Cloud, Exploring Data Transformation with Google Cloud, Innovating with Google Cloud Artificial Intelligence, Modernize Infrastructure and Applications with Google Cloud, Trust and Security with Google Cloud, Scaling with Google Cloud Operations.
Interactive Learning: Practice explaining Google Cloud capabilities in business language through discussion and scenario prompts. Comprehensive Study Materials: Structured coverage of all six official exam-guide sections, including data, AI, security, and operations. Real-World Applications: Map IaaS/PaaS/SaaS, migration paths, and AI options to situations leaders actually sponsor. Certification Preparation: Guidance for the Cloud Digital Leader exam focused on conceptual fluency, not deep configuration.
Upon completing the Google Cloud Digital Leader Certification Training Course with Accumentum, you will be prepared to take the official Cloud Digital Leader exam. The credential shows you can articulate Google Cloud core products and services and how they support enterprise goals. Accumentum does not invent exam prices or passing scores. Confirm current exam logistics on Google’s certification site when you schedule.
Use Accumentum’s registration page to enroll in Google Cloud Digital Leader Certification Training. Select the course, your funding option, and how you discovered Accumentum, then submit. You can also request guidance through Accumentum’s contact page.
Google lists 90 minutes for 50 to 60 multiple choice and multiple select questions.
Google lists a registration fee of $99, plus tax where applicable.
Google offers it in English, Japanese, Spanish, Portuguese and French.
Yes. You can take an online proctored exam from a remote location or an onsite proctored exam at a testing center.
Google's retake policy for foundational exams allows a maximum of ten attempts within a one year period, with at least 14 days between each failed attempt.
Foundational and associate certifications can be renewed starting 180 days before the expiration date. Google lets you renew by taking the standard exam, a shorter renewal exam or completing designated courses or skill badges in Google Skills.
Google lists a validity period of 3 years.
Yes. CDL prep is eligible for PathPay. Terms of 3, 4 and 6 months add no fee, and longer terms add 5% to 15%.
Enrollment
Enroll in Google Cloud Digital Leader Certification Training Course with Accumentum.
Use Accumentum’s registration page to enroll in Google Cloud Digital Leader Certification Training. Select the course, your funding option, and how you discovered Accumentum, then submit.
Use Accumentum’s registration page to enroll, or request guidance through the contact page.
Start Digital Leader training with Accumentum.
Use Accumentum’s registration page to enroll in Google Cloud Digital Leader Certification Training.