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AI+ Cloud™

  • Cloud-AI Fusion: Learn to integrate AI into scalable cloud environments
  • Advanced Infrastructure: Master CI/CD, cloud AI models, and deployment strategies
  • Capstone Project: Gain hands-on experience with real-world applications
  • Future-Ready Skills: Prepares professionals to lead AI-powered cloud innovation
Enroll Now
AI+ Cloud™
Self-Paced Online
USD $ 540.00
Instructor-Led Online
USD $ 4250.00

At a Glance: Course + Exam Overview

Our training approach is human‑centred and outcomes‑driven. We focus on what learners can apply confidently.

Category
AI Cloud
AI Technical
All Courses
Cloud Architect
DevOps Engineer
English
Language
Program Name
AI+ Cloud™
Duration
  • Instructor‑Led: 5 Days
  • Self‑Paced: 30 hours of content
Prerequisites
    • 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.
Exam Format
Exam details not available.

What You'll Learn

AI Model Development

Students learn to construct, train, and optimize machine learning models utilizing cloud-based tools and services. This involves learning to choose methods, preprocess data, and optimize models.

Mastering cloud AI model deployment

Learners will master cloud AI model deployment and integration into existing systems and workflows. Learn deployment pipelines, version control, and CI/CD procedures to seamlessly integrate AI solutions into production environments.

Problem-Solving in AI and Cloud

You will learn to apply AI and cloud computing concepts to real-world problems, enhancing their problem-solving skills.

Optimization Techniques

Emphasizing AI model development and cloud deployment, learners will learn to optimize AI models and processes for performance, scalability, and cost.

Certification Modules

Course Overview

  1. Course Introduction Preview

Module 1: Fundamentals of Artificial Intelligence (AI) and Cloud

  1. 1.1 Introduction to AI and Its Application
  2. 1.2 Overview of Cloud Computing and Its Benefits
  3. 1.3 Benefits and Challenges of AI-Cloud Integration

Module 2: Introduction to Artificial Intelligence

  1. 2.1 Basic Concepts and Principles of AI
  2. 2.2 Machine Learning and Its Applications
  3. 2.3 Overview of Common AI Algorithms
  4. 2.4 Introduction to Python Programming for AI

Module 3: Fundamentals of Cloud Computing

  1. 3.1 Cloud Service Models
  2. 3.2 Cloud Deployment Models
  3. 3.3 Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)

Module 4: AI Services in the Cloud

  1. 4.1 Integration of AI Services in Cloud Platform
  2. 4.2 Working with Pre-built Machine Learning Models
  3. 4.3 Introduction to Cloud-based AI tools

Module 5: AI Model Development in the Cloud

  1. 5.1 Building and Training Machine Learning Models
  2. 5.2 Model Optimization and Evaluation
  3. 5.3 Collaborative AI Development in a Cloud Environment

Module 6: Cloud Infrastructure for AI

  1. 6.1 Setting Up and Configuring Cloud Resources
  2. 6.2 Scalability and Performance Considerations
  3. 6.3 Data Storage and Management in the Cloud

Module 7: Deployment and Integration

  1. 7.1 Strategies for Deploying AI Models in the Cloud
  2. 7.2 Integration of AI Solutions with Existing Cloud-Based Applications
  3. 7.3 API Usage and Considerations

Module 8: Future Trends in AI+ Cloud Integration

  1. 8.1 Introduction to Future Trends
  2. 8.2 AI Trends Impacting Cloud Integration

Module 9: Capstone Project

  1. 9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem

Optional Module: AI Agents for Cloud Computing

  1. 1. Understanding AI Agents
  2. 2. Case Studies
  3. 3. Hands-On Practice with AI Agents

Finish the course and get certified

certificate

Industry Opportunities

Opportunity Image

Cloud AI Integration Specialist

Focuses on integrating AI tools into cloud systems, optimizing cloud performance, scalability, and security.

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AI Cloud Architect

Designs AI-powered cloud infrastructure, creating scalable, efficient, and secure cloud environments for organizations.

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Cloud Automation Expert

Implements AI-driven automation tools for managing cloud infrastructure, reducing manual intervention and improving operational efficiency.

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AI Cloud Data Scientist

Uses AI algorithms and data analytics to analyze cloud-based data, providing insights for better decision-making and resource management.

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Cloud Security AI Specialist

AI technologies are applied to enhance cloud security, detecting anomalies, predicting threats, and ensuring robust protection of cloud.

Frequently Asked Questions

How is the course structured?
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
Who should enroll in this certification?
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
What practical skills will I gain from this course?
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.
How does this certification benefit my career?
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.
What kind of projects will I work on during the course?
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.

Prerequisites

  • 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.

Exam Details

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

Exam Blueprint

Fundamentals of Artificial Intelligence (AI) and Cloud 5%
Introduction to Artificial Intelligence 7%
Fundamentals of Cloud Computing 8%
AI Services in the Cloud 10%
AI Model Development in the Cloud 15%
Cloud Infrastructure for AI 15%
Deployment and Integration 15%
Future Trends in AI + Cloud Integration 20%
Capstone 5%
Self-Paced Online

Self-Paced: 40 hours of content

USD $ 540.00
Purchase Self-Paced Course
Instructor-Led Online

Instructor-Led: 5 days (live or virtual)

USD $ 4250.00
Purchase Instructor-Led Course

Core AI Tools Covered

TensorFlow

TensorFlow

SHAP (SHapley Additive exPlanations)

SHAP (SHapley Additive exPlanations)

Amazon S3

Amazon S3

AWS SageMaker

AWS SageMaker