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AI Careers & Workforce Development

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
Price
NZ $0.00

All prices are in NZD, ex GST (15%).

At a Glance: Course + Exam Overview

Category AI Careers & Workforce Development Program Name: AI+ Cloud™
Exam Format 50 questions, 70% passing, 90 Minutes Duration:
  • Instructor-Led: 5 Days
  • Self-Paced: 30 hours of content

🤝 You’re never on your own — Parasol Concierge Support provides integration guidance and expert VA assistance so you can focus on mastering skills while we handle the setup details.

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

  1. Course Introduction Preview

  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

  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

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

  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

  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

  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

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

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

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

Industry opportunities

Cloud AI Integration Specialist

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

AI Cloud Architect

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

Cloud Automation Expert

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

AI Cloud Data Scientist

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

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

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.

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.

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.

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

Duration

90 Minutes

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%

Instructor-Led (Live Virtual/Classroom)

  • 5 days of intensive training with live demos
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners

Instructor-Led Course

🚀 Learn directly from certified AI trainers in live, interactive sessions. Get real-time guidance, practical exercises, and the accountability of a structured classroom experience. Perfect for professionals who want expert support and a clear path to certification.

✨ At Parasol Virtual, we go beyond certification. Our team supports your learning journey with guidance, resources, and local assistance to ensure your success. You’re not learning alone — you’re part of a global community with local support.

Request Virtual Training

Self-Paced Online

  • ~30 hours of on-demand video lessons, e-book, podcasts, and interactive labs
  • Learn anywhere, anytime, with modular quizzes to track progress

Self-Paced Course

🌐 Study anytime, anywhere with 24/7 access to course materials, practice tests, and resources. Move at your own speed while still working towards globally recognized certification. Designed for busy learners who value flexibility without compromising quality.

✨ At Parasol Virtual, we go beyond certification. Our team supports your learning journey with guidance, resources, and local assistance to ensure your success. You’re not learning alone — you’re part of a global community with local support.

Purchase Self-Paced Course

TECHNOLOGIES USED

TensorFlow
TensorFlow
SHAP (SHapley Additive exPlanations)
SHAP (SHapley Additive exPlanations)
Amazon S3
Amazon S3
AWS SageMaker
AWS SageMaker