Course

Introduction to Cloud-based AI

Learning path outcomes

  • Evaluate and implement cloud-based AI services for text, image, and audio processing tasks.
  • Compare and contrast different AI platforms and their capabilities in solving real-world problems.
  • Design and develop basic AI apps using cloud-based services and APIs. 

Prerequisites

 While the program is designed to accommodate developers with varying levels of experience, the following prerequisites are recommended: 
  • Basic programming knowledge in any language 
  • Familiarity with web development concepts and RESTful APIs 
  • Understanding of basic AI and machine learning concepts (beneficial but not required)

Achievements

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Introduction to Cloud-based AI

Learning path content

1
Text Generation with OpenAI
This module focuses on a basic text-generation app using OpenAI’s GPT-4 and the Chat Completions API. You’ll learn about API integration, model selection, and fundamental concepts in working with large language models.
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2
Text Generation with Google Gemini
Explore text generation using Google’s Gemini service. Learn about Google’s AI ecosystem and gain experience in implementing Gemini’s text generation capabilities.
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3
Multimodal Integration with OpenAI
This module extends students’ knowledge to multimodal AI apps, incorporating image and audio processing using OpenAI’s services. Students will learn to analyze images, generate and edit images, and work with speech recognition and synthesis.
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