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This course is designed for security professionals, AI engineers, and cybersecurity leaders looking to safeguard AI applications, models, and data infrastructure. The curriculum offers an in-depth exploration of AI and cloud computing, encompassing advanced cloud infrastructure and AI model deployment. Participants gain practical insights into cloudbased AI applications, culminating in an interactive capstone project.

Prerequisites

  • Basic understanding of AI and cloud computing principles
  • Familiarity with programming, data structures, and algorithms
  • Knowledge of cloud platforms such as AWS, Azure, or Google Cloud
  • Understanding of machine learning fundamentals and their application in cloud systems

 
Recertification Requirements
    To maintain the validity of your certification, The Whiteboard, in affiliation with AI CERTs, requires annual recertification. A notification will be sent three months before the due date, guiding candidates through the process outlined in the candidate handbook. Need Assistance? For any questions or support regarding recertification, please contact The Whiteboard's team at info@thewhiteboard.co.in.

Course Modules and Curriculum

Course Introduction Preview
  • 1.1 Introduction to AI and Its Application
  • 1.2 Overview of Cloud Computing and Its Benefits
  • 1.3 Benefits and Challenges of AI-Cloud Integration
  • 2.1 Basic Concepts and Principles of AI
  • 2.2 Machine Learning and Its Applications
  • 2.3 Overview of Common AI Algorithms
  • 2.4 Introduction to Python Programming for AI
  • 3.1 Cloud Service Models
  • 3.2 Cloud Deployment Models
  • 3.3 Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)
  • 4.1 Integration of AI Services in Cloud Platform
  • 4.2 Working with Pre-built Machine Learning Models
  • 4.3 Introduction to Cloud-based AI tools
  • 5.1 Building and Training Machine Learning Models
  • 5.2 Model Optimization and Evaluation
  • 5.3 Collaborative AI Development in a Cloud Environment
  • 6.1 Setting Up and Configuring Cloud Resources
  • 6.2 Scalability and Performance Considerations
  • 6.3 Data Storage and Management in the Cloud
  • 7.1 Strategies for Deploying AI Models in the Cloud
  • 7.2 Integration of AI Solutions with Existing Cloud-Based Applications
  • 7.3 API Usage and Considerations
  • 8.1 Introduction to Future Trends
  • 8.2 AI Trends Impacting Cloud Integration
  • 9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem

Tools

TensorFlow

TensorFlow

Amazon S3

Amazon S3

AWS SageMaker

AWS SageMaker

SHAP (SHapley Additive exPlanations)

SHAP (SHapley Additive exPlanations)

Who Should Enroll?

This certification is ideal for:

  • Developers & IT professionals
    - Looking to integrate AI with cloud platforms.
  • Cloud engineers & data scientists
    - Aiming to enhance their expertise in AI-driven cloud applications.
  • AI & ML enthusiasts
    - Seeking practical skills in deploying AI models on cloud infrastructure.
  • Professionals using AWS, Azure, or Google Cloud
    - For AI model development and deployment.
Key Learning Outcomes
  • AI Model Development: Learn to build, train, and optimize machine learning models using cloud-based tools.
  • Cloud AI Deployment: Understand deployment pipelines, version control, and CI/CD for seamless integration.
  • Real-World Problem Solving: Apply AI and cloud concepts to industry-specific challenges.
  • Optimization Techniques: Improve model efficiency, scalability, and cost-effectiveness.

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Exam Objectives

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AI Model Development

Assessing your ability to build, train, and optimize machine learning models using cloud-based tools and services.

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Cloud AI Model Deployment Mastery

Evaluating your skills in deploying AI models within cloud environments and integrating them into existing systems and workflows.

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AI and Cloud Problem-Solving

Testing your capability to apply AI and cloud computing concepts to solve real-world problems.

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Optimization Techniques

Measuring your understanding of optimizing AI models and processes for performance, scalability, and cost within cloud ecosystems.

Career Opportunities Post-Certification

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Median Salaries

$80,383

AI Salary Icon

With AI Skills

$141,310

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% Difference

76

Product Manager

Solutions Executive

Strategically design and implement AI solutions using cloud services to optimize performance and scalability across various applications and industries.

Data Analyst

Cloud Services Developer

Integrate machine learning models and scale AI applications on cloud platforms for efficient deployment and management.

AI Architect

Cloud Integration Specialists

Ensure seamless interoperability and optimal performance by integrating AI technologies with cloud services in complex environments.

ML Engineer

Cloud Solutions Developers

Leverage machine learning and cloud infrastructure to create customized AI solutions that enhance business operations and drive innovation.

Join AI Course & Become Future-Ready!

Stay ahead in the AI-driven world. Enroll now to gain in-demand skills, hands-on experience, and industry-recognized certification for a future-ready career.

Get Certified | Check Matching Certification To Your Career

Frequently Asked Questions

The course combines theoretical knowledge with practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.

This course is designed for developers, IT professionals, and individuals with a foundational understanding of AI and cloud computing who wish to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.

Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.

This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.

The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.