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Catalog > All Topics

AI+ Cloud (AI+ Cloud)

AI CERTS
  • Course Summary
  • Schedule
5 Days
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$3,995.00
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    • T87168
    • 5 days
    • 06/23/2025 - 06/27/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
    • Presented via WebEx
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    • T87169
    • 5 days
    • 07/21/2025 - 07/25/2025*
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    • T87170
    • 5 days
    • 08/18/2025 - 08/22/2025*
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    • T87171
    • 5 days
    • 09/22/2025 - 09/26/2025*
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    • T87172
    • 5 days
    • 10/20/2025 - 10/24/2025*
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    • T87173
    • 5 days
    • 11/17/2025 - 11/21/2025*
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    • T87174
    • 5 days
    • 12/15/2025 - 12/19/2025*
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Course Summary
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Description

Master the future of AI and cloud computing with AI Cloud Course. This comprehensive AI Cloud course will teach you how to effectively integrate AI and cloud computing using advanced strategies and real-world use cases. Learn how AI and cloud can work together to optimize your infrastructure, improve scalability, and drive innovation. Enroll today to earn your cloud AI certification while gaining practical skills in AI cloud computing, data management, and more.

The AI+ Cloud Course explores how Artificial Intelligence integrates with cloud computing to enhance data management and efficiency. It covers AI and cloud technologies, including major providers like AWS, Azure, and Google Cloud. Participants will develop and optimize AI models in the cloud and work with cloud-based AI tools. The course includes hands-on projects for building and deploying machine learning models. This training equips professionals to leverage cloud-based AI solutions and stay ahead of future trends.

 

Objectives

  • Enhance Efficiency
  • Scalability and Flexibility
  • Intelligent Insights and Decision Making
  • Enhanced Security and Compliance
  • Seamless Integration and Collaboration
  • Cost Optimization
  • Customer Experience Enhancement
  • Continuous Improvement and Innovation

Prerequisites

Required

  • A foundational understanding of key concepts in both artificial intelligence and cloud computing
  • Fundamental understanding of computer science concepts like programming, data structures, and algorithms
  • Familiarity with cloud computing platforms like AWS, Azure, or GCP
  • Basic knowledge of mathematics as it important for machine learning, which is a core component of AI+ Cloud program

​Recommended

  • AI+ Executive
  • AI+ Everyone

Who Should Attend

  • IT Professional
  • Cloud Developer

Outline

Fundamentals of Artificial Intelligence (AI) and Cloud

  • Introduction to AI and Its Application
  • Overview of Cloud Computing and Its Benefits
  • Benefits and Challenges of AI-Cloud Integration

Introduction to Artificial Intelligence

  • Basic Concepts and Principles of AI
  • Machine Learning and Its Applications
  • Overview of Common AI Algorithms
  • Introduction to Python Programming for AI

Fundamentals of Cloud Computing

  • Cloud Service Models
  • Cloud Deployment Models
  • Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)

AI Services in the Cloud

  • Integration of AI Services in Cloud Platform
  • Working with Pre-built Machine Learning Models
  • Introduction to Cloud-based AI tools

AI Model Development in the Cloud

  • Building and Training Machine Learning Models
  • Model Optimization and Evaluation
  • Collaborative AI Development in a Cloud Environment

​

Cloud Infrastructure for AI

  • Setting Up and Configuring Cloud Resources
  • Scalability and Performance Considerations
  • Data Storage and Management in the Cloud

Deployment and Integration

  • Strategies for Deploying AI Models in the Cloud
  • Integration of AI Solutions with Existing Cloud-Based Applications
  • API Usage and Considerations

Future Trends in AI+ Cloud Integration

  • Introduction to Future Trends
  • AI Trends Impacting Cloud Integration

Capstone Project

  • Exercise 1: Diabetes Prediction Using Machine Learning
  • Exercise 2: Building & Deploying an Image Classification Web App with GCP AutoML Vision Edge, Tensorflow.js & GCP App Engine
  • Exercise 3: How to deploy your own ML model to GCP in 5 simple steps.
  • Exercise 4: Google Cloud Platform Custom Model Upload , REST API Inference and Model Version Monitoring
  • Exercise 5: Deploy Machine Learning Model in Google Cloud Platform Using Flask

Optional Module: AI Agents for Cloud Computing

  • Understanding AI Agents
  • Case Studies
  • Hands-On Practice with AI Agents

 

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