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AI+ Cloud™ - Chinese
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Introduction
Course Introduction
Lab Instructions
Audio Book: Introduction AI+ Cloud
Module 01: Fundamentals of AI and Cloud
1.1 Understanding Artificial Intelligence
1.2 Applications of AI
1.3 Understanding Cloud Computing
1.4 Key Benefits of Cloud Computing
1.5 Application of AI in Cloud Computing
1.6 Addressing Challenges in AI Cloud Integration
Module 1: Fundamentals of Artificial Intelligence (AI) and Cloud
Audio Book: Fundamentals of Artificial Intelligence (AI) and Cloud
Podcast: Fundamentals of AI and Cloud
Activity: True/False
Activity: Accordion
Activity: Drag and Drop
Activity: Knowledge checks
Quiz
Module 02: Introduction to Artificial Intelligence
2.1 Understanding the Foundations
2.2 Key Components of AI
2.3 Introduction to Machine Learning
2.4 Types of Machine Learning
2.5 Practical Applications of Machine Learning
2.6 Essential AI Algorithms
2.7 Python Basics for AI
2.8 Python Libraries for AI
Module 2: Introduction to Artificial Intelligence
Audio Book: Introduction to Artificial Intelligence
Podcast: Introduction to Artificial Intelligence
Activity: True/False
Activity: Tab Type 1
Activity: Scenario Activity
Activity: Multiple Response
Activity: Knowledge Checks
Quiz
Lab Practice 2.1
Lab Practice 2.2
Python File Download
Module 3: Fundamentals of Cloud Computing
3.1 Infrastructure as a Service
3.2 Platform-as-a-Service
3.3 Software as a Service
3.4 Types of Cloud Deployment Models
3.5 Public Cloud
3.6 Private Cloud
3.7 Hybrid Cloud
3.8 Hands-on Activity
3.9 AWS: Amazon's Cloud Ecosystem What
3.10 Azure: Microsoft's Cloud Solutions
3.11 Google Cloud: Innovation and Scalability
Module 3: Fundamentals of Cloud Computing
Audio Book: Fundamentals of Cloud Computing
Podcast: Fundamentals of Cloud Computing
Activity: Hotspot
Activity: Drag and Drop
Activity: True/False
Activity: Knowledge checks
Quiz
Lab Practice 3.1 - Azure Version
Lab Practice 3.1 - AWS Version
Lab Practice 3.1 - GCP Version
Download Data Set - Lab Practice 3.1
Lab Practice 3.2 - Azure Version
Lab Practice 3.2 - AWS Version
Module 4: AI Services in the Cloud
4.1 Overview of Cloud AI Services
4.2 Integrating Cloud AI Services
4.3 Leveraging Pre-built Models
4.4 Practical Application
4.5 Analyzing Results and Fine-tuning
4.6 Overview of Cloud-based AI Development Tools
Module 4: AI Services in the Cloud
Audio Book: AI Services in the Cloud
Podcast: AI Services in the Cloud
Activity: Problem Statement: Type 1
Activity: Carousel/Slideshow
Activity: True/False
Activity: Knowledge Checks
Quiz
Lab Practice 4.1 - Azure Version
Lab Practice 4.1 - AWS Vesrion
Lab Practice 4.1 - GCP Vesrion
Lab Practice 4.2 - Azure Version
Lab Practice 4.2 - AWS Version
Lab Practice 4.2 - GCP Version
Lab Practice 4.3 - Azure Version
Lab Practice 4.3 - GCP Version
Module 5: AI Model Development in the Cloud
5.1 Traditional Machine Learning Model Development
5.2 Building Machine Learning Models with AutoML
5.3 Hyperparameter Tuning: Delve into hyperparameter tuning techniques for optimizing model performance
5.4 Evaluation Metrics and Techniques
5.5 Interpretability and Explainability
5.6 Version Control for Machine Learning Projects
5.7 Collaborative Development Platforms
5.8 Model Deployment and Sharing
Module 5: AI Model Development in the Cloud
Audio Book: AI Model Development in the Cloud
Podcast: AI Model Development in the Cloud
Activity: Sequence
Activity: Multiple Response
Activity: True/False
Activity: Knowledge Checks
Quiz
Lab Practice 5.1
Lab Practice 5.2 - Azure Version
Lab Practice 5.2 - AWS Version
Lab Practice 5.2 - GCP Version
Lab Practice 5.3
Python File Download
Module 6: Cloud Infrastructure for AI
6.1 Infrastructure as Code (IaC)
6.2 GPU and TPU Utilization
6.3 Auto-Scaling Strategies
6.4 Data Security and Compliance
6.5 Data Lifecycle Management
Module 6: Cloud Infrastructure for AI
Audio Book: Cloud Infrastructure for AI
Podcast: Cloud Infrastructure for AI
Activity: PopUp
Activity: Problem Statement
Activity: Hotspot
Activity: Knowledge Checks
Quiz
Lab Practice 6.1 - Azure Version
Lab Practice 6.1 - AWS Version
Lab Practice 6.1 - GCP Version
Lab Practice 6.2 - Azure Version
Lab Practice 6.2 - AWS Version
Lab Practice 6.2 - GCP Version
Module 7: Deployment and Integration
7.1 Popular Deployment Strategies & Pattern
7.2 Platform-Specific Deployment
7.3 Cloud Application Architecture
7.4 Microservices and AI
7.5 Data Integration Considerations
7.6 API Design for AI Services
7.7 Testing Apis: Learn Testing Apis Through Various Tools Like Postman or Other Tool
Module 7: Deployment and Integration
Audio Book: Deployment and Integration
Podcast: Deployment and Integration
Activity: Tab: Type 2
Activity: Case Study
Activity: Multiple choice with image
Activity: Knowledge checks
Quiz
Module 8: Future Trends in AI+ Cloud Integration
8.1 Introduction to Explainable AI or XAI
8.2 Federated Learning
8.3 AI for Good
8.4 Quantum Computing and AI
8.5 Edge AI and Hybrid Cloud
8.6 Serverless AI
8.7 AutoML and Automated MLOps
8.8 Responsible AI in the Cloud
Module 8: Future Trends in AI + Cloud Integration
Audio Book: Future Trends in AI+ Cloud Integration
Podcast: Future Trends in AI+ Cloud Integration
Activity: Sequence
Activity: Problem Statement
Activity: Knowledge Checks
Quiz
Module 9: Hands on Examples
9.1 Applying AI and Cloud Concepts to Solve a Real-World Problem
Module 9: Hands on Examples
Audio Book: Hands on Examples
Podcast: Hands on Examples
Activity: Tab Type 3
Activity: Knowledge Checks
Lab Practice 9.1
Lab Practice 9.2 - Azure Version
Lab Practice 9.2 - GCP Version
Python File Download
Course Summary
Course Summary
AI Agent Cloud
1.1 AI Agents in Cloud Services: Examples and Their Growing Significance
1.2 Emerging Trends and the Importance of AI Agents in Cloud Services
1.3 Types of AI Agents in Cloud Services
1.4 Case Studies in AI-Powered Cloud Scaling Solutions
Graded Assessment- 5 Questions
Resources
AI+ Cloud Blueprint
AI+ Cloud Detailed Curriculum
AI+ Cloud Tools
AI+ Cloud Resources and References
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Cloud Examination
AI+ Cloud Examination
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