Our comprehensive Cloud training programs cover all major platforms including Google Cloud, HUAWEI Cloud, Oracle Cloud, and AWS.
Cloud Computing
Training Programs
Program Overview
This intensive training program spans 40 credit hours, delivered across 10 sessions of 4 hours each. The program is designed for individuals who have some foundational cloud knowledge and are looking to advance their skills in Google Cloud Platform (GCP) to an Associate level. We will focus on both theoretical understanding and hands-on experience to ensure participants are job-ready.
Training Objectives
Upon completion of this training program, participants will be able to:
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Architect Basic Cloud Solutions: Design and implement simple cloud solutions using core GCP services.​
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Manage Compute Resources: Effectively manage and scale compute resources using Compute Engine and related services.​
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Implement Storage Solutions: Utilize various GCP storage options based on different needs and requirements.​
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Configure Networking: Configure and manage Virtual Private Cloud (VPC) networks for cloud environments.​
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Work with Managed Databases: Deploy and manage relational and non-relational databases using Cloud SQL and other database options.​
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Understand Data Analytics: Explore data analytics capabilities with BigQuery.​
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Deploy and Manage Applications: Deploy and manage applications using App Engine, Kubernetes Engine, and other relevant services.​
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Implement Cloud Security Best Practices: Apply key security concepts and tools within GCP.​
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Prepare for Google Cloud Associate Certification: Lay a solid foundation for pursuing relevant Google Cloud certifications at the Associate level.
Program Overview
This rigorous training program spans 60 credit hours, delivered across 20 sessions of 3 hours each. The program is designed for individuals with significant experience with Google Cloud Platform (GCP) and seeking to elevate their skills to a professional level. We will emphasize advanced concepts, best practices, and hands-on implementation of complex solutions.
Training Objectives
Upon completion of this training program, participants will be able to:
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Design Complex Cloud Solutions: Architect, design, and implement complex and scalable cloud solutions using a wide range of GCP services.
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Manage Scalable Compute Infrastructure: Effectively manage, scale, and optimize compute resources including Kubernetes Engine (GKE), Compute Engine, and serverless options.
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Implement Advanced Storage and Data Management: Utilize and manage a diverse range of storage options and implement effective data management strategies.
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Configure Advanced Networking Scenarios: Design and implement complex Virtual Private Cloud (VPC) architectures including hybrid connectivity and security measures.
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Work with Specialized Databases and Data Analytics: Deploy, manage, and optimize specialized databases, and conduct advanced data analytics using BigQuery.
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Manage DevOps Processes: Implement CI/CD pipelines, automation, and Infrastructure as Code (IaC) within the GCP environment.
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Implement Robust Cloud Security: Design, implement, and manage advanced security measures, including IAM, encryption, and vulnerability management.
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Optimize Cloud Resources: Implement cost optimization and resource management strategies to maximize efficiency.
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Prepare for Google Cloud Professional Certification: Lay a solid foundation for pursuing relevant Google Cloud certifications at the Professional level.
Program Overview
This robust training program spans 60 credit hours, delivered across 20 sessions of 3 hours each. The program is designed to provide a foundational understanding of Google Cloud core services alongside practical skills in leveraging AI tools and services offered by Google Cloud.
This is a "one-level" program meaning it provides both cloud fundamentals and an introduction to AI on the platform without specifically targeting associate or professional level certification.
Training Objectives
Upon completion of this training program, participants will be able to:
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Understand Core Google Cloud Concepts: Grasp the fundamentals of Google Cloud Platform (GCP) architecture, services, and pricing models.
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Utilize Core GCP Services: Effectively use essential GCP services, such as Compute Engine, Cloud Storage, and Virtual Private Cloud (VPC).
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Explore AI Concepts and Google Cloud AI: Understand fundamental AI and Machine Learning concepts and how they apply to real-world problems.
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Use Vertex AI Platform: Create and manage Machine Learning models using Google's Vertex AI platform.
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Work with Google Cloud AI Services: Leverage popular Google Cloud AI services such as Vision AI, Natural Language AI, and Translation AI.
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Integrate Gemini API: Learn to integrate the Gemini API into web and mobile applications.
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Apply AI to Practical Scenarios: Understand how to apply AI and machine learning to solve real-world business problems and workflows.
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Implement Basic Cloud and AI Security Practices: Understand basic security considerations within a cloud environment and AI applications.
Program Overview
This robust training program spans 30 credit hours, delivered across 10 sessions of 3 hours each. The program is designed to provide a foundational understanding of Google Cloud core services alongside practical skills in leveraging AI tools and services offered by Google Cloud.
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This "one-level" program provides both cloud fundamentals and an introduction to AI on the platform without specifically targeting associate or professional-level certification.
Training Objectives
Upon completion of this training program, participants will be able to:
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Understand Core Google Cloud Concepts: Grasp the fundamentals of Google Cloud Platform (GCP) architecture and essential services.
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Utilize Core GCP Services: Use essential GCP services, such as Compute Engine, Cloud Storage, and Virtual Private Cloud (VPC).
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Explore AI Concepts and Google Cloud AI: Understand fundamental AI and Machine Learning concepts relevant to practical applications.
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Use Vertex AI Platform: Train and deploy basic Machine Learning models using Vertex AI.
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Work with Select Google Cloud AI Services: Leverage popular Google Cloud AI services such as Vision AI or Natural Language AI.
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Integrate Gemini API: Learn how to use the Gemini API for specific use cases.
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Apply AI to Simple Scenarios: Understand how to approach basic problems with AI and machine learning solutions.
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Understand Basic Security Practices: Know basic security considerations in cloud and AI applications.
Program Overview
This intensive Oracle Associate Level Training Program spans 40 credit hours, delivered across 10 sessions of 4 hours each.
The program is designed for individuals seeking to gain a solid understanding of core Oracle concepts and practical application skills.
We prioritize hands-on learning, ensuring participants can translate theoretical knowledge into real-world practice.
Training Objectives
Upon completion of this training program, participants will be able to:
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Understand Oracle Cloud Infrastructure (OCI): Grasp the core concepts of Oracle's cloud platform, including its architecture and services.
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Navigate the OCI Console: Effectively use the OCI console to manage cloud resources.
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Deploy and Manage Compute Resources: Provision and manage virtual machines (VMs) and other compute instances in OCI.
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Utilize Oracle Cloud Databases: Interact with and manage Oracle database services in the cloud, such as Autonomous Database.
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Understand Cloud Networking: Grasp the fundamentals of networking within OCI, including virtual cloud networks (VCNs) and subnets.
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Work with Cloud Storage: Store and manage data using various OCI storage services.
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Implement Basic Cloud Security: Understand and apply basic security principles within OCI.
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Prepare for Oracle Cloud Associate Certification: Lay a solid foundation for pursuing relevant Oracle Cloud certifications at the Associate level.
Program Overview
This intensive training program spans 40 credit hours, delivered across 10 sessions of 4 hours each.
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It is designed for individuals who have a foundational understanding of cloud concepts and seek to develop associate-level proficiency within the AWS ecosystem.
We will balance theoretical learning with hands-on exercises to ensure participants gain practical skills and confidence.
Training Objectives
Upon completion of this training program, participants will be able to:
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Understand AWS Core Services: Grasp the fundamental concepts and key services offered by AWS.
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Manage Compute Resources: Provision, manage, and scale compute resources using services like EC2 and Lambda.
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Implement Storage Solutions: Utilize various AWS storage options based on application needs.
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Configure Networking: Create and manage Virtual Private Clouds (VPCs) and related networking resources.
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Work with Managed Databases: Deploy, manage, and connect to managed database services like RDS and DynamoDB.
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Understand Security and Compliance: Implement basic security best practices and understand compliance within AWS.
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Deploy and Manage Applications: Deploy and manage applications using services like Elastic Beanstalk and ECS.
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Utilize Monitoring and Logging: Leverage AWS monitoring and logging tools to enhance resource management.
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Prepare for AWS Certified Cloud Practitioner or Associate Level Certification: Lay a solid foundation for pursuing relevant AWS certifications at the entry or associate levels.
Program Overview
This rigorous training program spans 60 credit hours, delivered across 20 sessions of 3 hours each.
The program is designed for individuals who have substantial experience with cloud platforms and are seeking to deepen their skills on Huawei Cloud.
We will focus on advanced concepts, best practices, and hands-on implementation of complex solutions within the Huawei Cloud ecosystem.
Training Objectives
Upon completion of this training program, participants will be able to:
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Architect Complex Cloud Solutions: Design and implement complex, scalable cloud solutions using a wide array of Huawei Cloud services.
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Manage Scalable Compute Infrastructure: Effectively manage and optimize compute resources, including Elastic Cloud Servers (ECS), container services, and serverless options.
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Implement Advanced Storage and Data Management: Utilize and manage various storage services and implement effective data management strategies.
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Configure Advanced Networking Scenarios: Design and implement complex Virtual Private Cloud (VPC) architectures with advanced networking features.
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Work with Specialized Databases and Big Data Solutions: Deploy, manage, and optimize specialized databases, and conduct big data analytics using Huawei Cloud offerings.
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Manage DevOps Processes: Implement CI/CD pipelines, automation, and Infrastructure as Code (IaC) within the Huawei Cloud environment.
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Implement Robust Cloud Security: Design, implement, and manage advanced security measures, including Identity and Access Management (IAM), encryption, and vulnerability management.
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Optimize Cloud Resources: Implement cost optimization and resource management strategies to maximize efficiency on Huawei Cloud.
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Prepare for Huawei Cloud Professional Certifications: Lay a solid foundation for pursuing relevant Huawei Cloud certifications at the Associate level like, HCIA-Cloud Computing & HCCDA-Tech Essentials.
Program Overview
This intensive training program spans 40 credit hours, delivered across 10 sessions of 4 hours each.
It is designed for individuals who have a foundational understanding of technology and are seeking to gain associate-level proficiency within the Microsoft Azure ecosystem. We will use a blend of theoretical explanations, practical demonstrations, and hands-on exercises to ensure participants gain both theoretical understanding and practical skills.
Training Objectives
Upon completion of this training program, participants will be able to:
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Understand Core Cloud Concepts: Grasp the fundamentals of cloud computing principles, models, and benefits.
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Understand Azure Core Services: Comprehend the breadth of Azure services and their applications.
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Understand Azure Architecture and Management: Gain knowledge of Azure's infrastructure, management tools, and resource deployment strategies.
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Manage Azure Compute Resources: Provision, manage, and scale virtual machines, containers, and serverless functions.
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Implement Storage Solutions: Utilize various Azure storage services to store and manage data effectively.
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Configure Networking: Create and manage Virtual Networks (VNets) and networking resources within Azure.
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Understand Azure Security, Identity, and Governance: Implement security best practices, manage identities, and apply governance policies within Azure.
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Manage Azure Resources with the Azure Portal and PowerShell: Gain proficiency in using the Azure Portal and PowerShell for resource management.
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Prepare for the Azure Fundamentals (AZ-900) Exam: Develop a solid foundation of Azure concepts, preparing them to pass the AZ-900 exam.
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Prepare for the Azure Administrator (AZ-104) Exam: Gain the knowledge and skills necessary to manage Azure resources effectively, preparing them for the AZ-104 exam.
Program Overview
This rigorous training program spans 60 credit hours, delivered across 20 sessions of 3 hours each.
The program is designed for experienced IT professionals with a solid understanding of cloud concepts and Azure fundamentals, who are seeking to elevate their skills to the expert level. We will use a combination of in-depth lectures, real-world case studies, hands-on labs, and architectural design exercises to prepare participants for the challenges of designing and implementing complex Azure solutions.
Training Objectives
Upon completion of this training program, participants will be able to:
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Design Azure Solutions: Architect and design complex, scalable, secure, and cost-effective solutions on Azure.
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Assess Workload Requirements: Analyze business requirements, technical requirements, and performance requirements to design appropriate Azure solutions.
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Design for Identity, Security, and Compliance: Design security strategies, implement identity management solutions, and ensure compliance with regulatory requirements.
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Design Data Storage Solutions: Recommend and design appropriate data storage solutions, including relational databases, NoSQL databases, and data lakes.
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Design Business Continuity Solutions: Design solutions for disaster recovery, backup, and high availability.
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Design Infrastructure Solutions: Design networking, compute, and migration strategies for Azure environments.
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Integrate DevOps Practices: Incorporate DevOps principles and automation into Azure solutions.
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Design for Cost Optimization: Recommend strategies for optimizing costs and maximizing ROI in Azure deployments.
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Prepare for the Azure Solutions Architect Expert (AZ-305) Exam: Gain the knowledge and skills necessary to pass the AZ-305 exam and achieve the Azure Solutions Architect Expert certification.
