AI Cloud Training
| Commitment | 5 Days, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
The AI Cloud Training 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.
WHAT'S INCLUDED?
- 5 days of AI Cloud Training with an expert instructor
- AI Cloud Training Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- AI Cloud Training – https://www.wiley.com/
- AI Cloud Training – https://www.packtpub.com/
- AI Cloud – https://store.logicaloperations.com/
- AI Cloud Training – https://us.artechhouse.com/
- AI Cloud Training – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this AI Cloud Training course, participants can:
- 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.
CUSTOMIZE IT
- We can adapt this AI Cloud Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this AI Cloud Training course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the AI Cloud Training course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the AI Cloud Training course in a manner understandable to lay audiences.
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this AI Cloud Training course are:
- 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
AUDIENCE/TARGET GROUP
The target audience for this AI Cloud Training course:
- All
COURSE SYLLABUS
Module 1: Fundamentals of Artificial Intelligence (AI) in Cloud
- Introduction to AI and Its Application
- Overview of Cloud Computing and Its Benefits
- Benefits and Challenges of AI-Cloud Integration
Module 2: Introduction to Artificial Intelligence
- Basic Concepts and Principles of AI
- Machine Learning and Its Applications
- Overview of Common AI Algorithms
- Introduction to Python Programming for AI
Module 3: Fundamentals of Cloud Computing
- Cloud Service Models
- Cloud Deployment Models
- Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)
Module 4: AI Services in the Cloud
- Integration of AI Services in Cloud Platform
- Working with Pre-built Machine Learning Models
- Introduction to Cloud-based AI tools
Module 5: AI Model Development in the Cloud
- Building and Training Machine Learning Models
- Model Optimization and Evaluation
- Collaborative AI Development in a Cloud Environment
Module 6: Cloud Infrastructure for AI
- Setting Up and Configuring Cloud Resources
- Scalability and Performance Considerations
- Data Storage and Management in the Cloud
Module 7: Deployment and Integration
- Strategies for Deploying AI Models in the Cloud
- Integration of AI Solutions with Existing Cloud-Based Applications
- API Usage and Considerations
Module 8: Future Trends in AI+ Cloud Integration
- Introduction to Future Trends
- AI Trends Impacting Cloud Integration
Module 9: Capstone Project
- Exercise 1: Diabetes Prediction Using Machine Learning
- Exercise 2: Building & Deploying an Image Classification Web App with GCP AutoML Vision Edge, Tensorflow.js & GCP App Engine
- Exercise 3: How to deploy your own ML model to GCP in 5 simple steps.
- Exercise 4: Google Cloud Platform Custom Model Upload , REST API Inference and Model Version Monitoring
- Exercise 5: Deploy Machine Learning Model in Google Cloud Platform Using Flask
