AI+ Cloud (AICL)

 

Course Overview

The AI+ Cloud™ certification program targets developers and IT professionals aspiring to excel in cloud computing integrated with artificial intelligence. 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 cloud-based AI applications, culminating in an interactive capstone project. With these skills, graduates are primed to navigate the dynamic AI+ Cloud™ integration landscape, equipped to design and implement AI solutions seamlessly within cloud environments for sustained success.

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

Course Objectives

  • 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
    • Participants will learn to apply AI and cloud computing concepts to real-world problems will improve 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.

Outline: AI+ Cloud (AICL)

Module 1: Fundamentals of Artificial Intelligence (AI) in 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 Integration

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

Module 9: Capstone Project

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

Prices & Delivery methods

Online Training

Duration
5 days

Price
  • Online Training: CAD 4,555
  • Online Training: US$ 3,450
Classroom Training

Duration
5 days

Price
  • Canada: CAD 4,555

Schedule

Currently there are no training dates scheduled for this course.