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AI+ Cloud Practitioner™

Course code: NPAT110

Formerly known as AI+ Cloud™

Transform Cloud Computing with Cutting-Edge AI integration

  • Cloud-AI Integration: Develop the skills to embed AI capabilities into scalable cloud infrastructures
  • Advanced Infrastructure: Build expertise in CI/CD pipelines, cloud-based AI models, and deployment strategies
  • Capstone Project: Apply knowledge through hands-on, real-world project experience
  • Future-Ready Skills: Equip yourself to drive and lead AI-powered innovation across cloud environments
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 30 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 30 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 30 hours en 285 EUR Register
G Upon request Self-paced 30 hours en 75 EUR Register
G Guaranteed course

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Course description

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.

Course structure

Course Overview

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

  • 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

Module 2: Introduction to Artificial Intelligence

  • 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

Module 3: Fundamentals of Cloud Computing

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

Module 4: AI Services in the 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

Module 5: AI Model Development in the Cloud

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

Module 6: Cloud Infrastructure for AI

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

Module 7: Deployment and Integration

  • 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

Module 8: Future Trends in AI+ Cloud Practitioner™ Integration

  • 8.1 Introduction to Future Trends
  • 8.2 AI Trends Impacting Cloud Integration

Module 9: Capstone Project

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

Optional Module: AI Agents for Cloud Computing

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

Prerequisites

  • A foundational grasp of core concepts across both artificial intelligence and cloud computing
  • Basic computer science knowledge, including programming fundamentals, data structures, and algorithms
  • Working familiarity with major cloud platforms such as AWS, Azure, or GCP
  • An understanding of foundational mathematics relevant to machine learning, which forms a central part of the AI+ Cloud™ program

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