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Course Outline

Overview of Artificial Intelligence and Generative AI

  • Core principles of AI and its influence on modern technology
  • Introduction to Generative AI mechanisms and use cases

Azure OpenAI Service Deployment

  • Configuration of an Azure OpenAI account
  • Review of Azure OpenAI quotas, pricing structures, and compliance policies

Operational Use of Azure OpenAI Studio

  • Interaction with the Azure OpenAI Studio interface
  • Deployment and management of Large Language Models (LLMs)

Integration of AI Models into Applications

  • Utilization of the Playground environment for model validation
  • Retrieval and deployment of models using Postman and Python APIs
  • Foundation of ChatGPT and techniques for Prompt Engineering

Advanced AI Methodologies

  • Fine-tuning AI models for specialized operational tasks
  • Image generation via DALL-E studio
  • Processing and implementation of text embeddings
  • Advanced Prompt Engineering strategies for optimized model interaction

AI Model Integration Strategies

  • Combination of text, image, and audio models for comprehensive applications
  • Audio transcription and text generation using Whisper AI

Security and Optimization of AI Deployments

  • Implementation of security protocols for AI-driven chat systems
  • Application of content filters to ensure data integrity

Project: Development of AI-Driven Solutions

  • Architecture design of a web application leveraging Azure OpenAI models
  • Integration of diverse AI capabilities into a unified system

Conclusion and Recommended Actions

Requirements

  • Knowledge of cloud computing platforms
  • Proficiency in Python programming
  • No previous AI experience is necessary

Target Audience

  • AI developers
  • AI professionals and stakeholders
 14 Hours

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