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WIZAPE
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10 Modules / ~100 pages
Wizard Mode
~25 Modules / ~400 pages

Cloud Computing Platforms for AI
( 30 Modules )

Module #1
Introduction to Cloud Computing
Overview of cloud computing, its advantages, and relevance to AI
Module #2
AI and Cloud Computing:A Perfect Match
How cloud computing enables AI development and deployment
Module #3
Cloud Service Models:IaaS, PaaS, SaaS
Understanding the different cloud service models and their applications in AI
Module #4
Cloud Deployment Models:Public, Private, Hybrid
Understanding the different cloud deployment models and their applications in AI
Module #5
AWS Overview for AI
Introduction to Amazon Web Services (AWS) and its AI services
Module #6
AWS SageMaker:Building, Training, and Deploying AI Models
Hands-on experience with AWS SageMaker for building, training, and deploying AI models
Module #7
Google Cloud AI Platform:Overview and Services
Introduction to Google Cloud AI Platform and its services for AI development
Module #8
Google Cloud AI Platform:AutoML, TensorFlow, and More
Hands-on experience with Google Cloud AI Platforms AutoML, TensorFlow, and other services
Module #9
Microsoft Azure Machine Learning:Overview and Services
Introduction to Microsoft Azure Machine Learning and its services for AI development
Module #10
Microsoft Azure Machine Learning:Azure Databricks, Cognitive Services, and More
Hands-on experience with Microsoft Azure Machine Learnings Azure Databricks, Cognitive Services, and other services
Module #11
IBM Cloud:Watson Studio and AI Services
Introduction to IBM Clouds Watson Studio and AI services for AI development
Module #12
Cloud-Based Data Storage for AI
Understanding cloud-based data storage options for AI applications
Module #13
Cloud-Based Data Processing for AI
Understanding cloud-based data processing options for AI applications
Module #14
Cloud Security and Compliance for AI
Understanding cloud security and compliance considerations for AI applications
Module #15
Migrating AI Workloads to the Cloud
Best practices for migrating AI workloads to the cloud
Module #16
Cloud Cost Optimization for AI
Understanding cloud cost optimization strategies for AI applications
Module #17
AI-Driven Cloud Automation
Using AI to automate cloud operations and management
Module #18
Cloud-Native AI Applications
Designing and building cloud-native AI applications
Module #19
AI-Powered Cloud Orchestration
Using AI to orchestrate cloud resources and services
Module #20
Cloud-Based AI for Computer Vision
Using cloud-based AI services for computer vision applications
Module #21
Cloud-Based AI for Natural Language Processing
Using cloud-based AI services for natural language processing applications
Module #22
Cloud-Based AI for Predictive Analytics
Using cloud-based AI services for predictive analytics applications
Module #23
Cloud-Based AI for IoT Applications
Using cloud-based AI services for IoT applications
Module #24
Cloud-Based AI for Edge Computing
Using cloud-based AI services for edge computing applications
Module #25
Real-World AI Use Cases in the Cloud
Exploring real-world AI use cases in the cloud across various industries
Module #26
Building a Cloud-Based AI Team
Building a team to develop and deploy AI applications in the cloud
Module #27
Cloud-Based AI Ethics and Fairness
Understanding AI ethics and fairness considerations in cloud-based AI applications
Module #28
Cloud-Based AI Governance and Risk Management
Understanding AI governance and risk management considerations in cloud-based AI applications
Module #29
Case Studies in Cloud-Based AI
Exploring real-world case studies of cloud-based AI applications
Module #30
Course Wrap-Up & Conclusion
Planning next steps in Cloud Computing Platforms for AI career


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