מה צריך לדעת לפני
שתתחיל

מתחיל 5 June 2026 08:06

נגמר 5 June 2026

00 ימים
00 שעות
00 דקות
00 שניות
course image

Full-stack AI Development with AWS Amplify AI Kit

Discover how to build generative AI applications by combining AWS Amplify, Amazon Q, and Bedrock for intelligent search, summarization, and chatbot features in full-stack development.
AWS Events via YouTube

AWS Events

6076 קורסים


39 minutes

שדרוג אופציונלי זמין

Not Specified

התקדמות בקצב שלך

Free Video

שדרוג אופציונלי זמין

סקירה כללית

Discover how to build generative AI applications by combining AWS Amplify, Amazon Q, and Bedrock for intelligent search, summarization, and chatbot features in full-stack development.

סילבוס

  • Introduction to Full-Stack AI Development
  • Overview of Full-Stack AI Applications
    Key Technologies: AWS Amplify, Amazon Q, and Bedrock
  • Setting Up Your Development Environment
  • Introduction to AWS Amplify
    Installing and Configuring AWS CLI
    Setting Up Amplify Project and Environment
  • Understanding Generative AI Concepts
  • Basics of Generative AI
    Use Cases in Search, Summarization, and Chatbots
  • Using AWS Amplify for Frontend Development
  • Building User Interfaces with Amplify
    Integrating Amplify Libraries for AI Features
  • Backend Development with AWS
  • Introduction to AWS Amplify Backend
    Configuring GraphQL APIs and Databases
    Using Authentication and Authorization
  • Deep Dive into Amazon Q and Bedrock
  • Setting Up Amazon Q for Intelligent Search
    Integrating Amazon Bedrock for Text Summarization
    Building AI-Powered Chatbots with Bedrock
  • Developing AI Features
  • Implementing Intelligent Search with Amazon Q
    Creating Text Summarization Services
    Building a Responsive Chatbot Interface
  • Testing and Deploying AI Applications
  • Strategies for Testing AI Models and Applications
    Using AWS Tools for Deployment and Monitoring
  • Real-World Application Development Project
  • Designing an Application with Generative AI Features
    Development Workflow and Best Practices
    Final Project Deployment and Presentation
  • Future Trends and Advanced Topics in AI
  • Exploring Beyond Basics: Machine Learning Integration
    Scalability and Performance Optimization
    Ethical Considerations and Data Privacy in AI
  • Conclusion and Course Wrap-Up
  • Recap of Key Learnings
    Additional Resources for Continued Learning

נושאים

Programming