Course 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.
Modules:
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 Platforms
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: Hands on Examples
9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem