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Course Outline

Introduction to AI and Generative AI

  • Foundational principles of AI and its transformative impact on technology.
  • Overview of Generative AI basics and its real-world applications.

Azure OpenAI Service Deployment

  • Initialization of an Azure OpenAI account.
  • In-depth analysis of Azure OpenAI quotas, pricing structures, and usage policies.

Working with Azure OpenAI Studio

  • Guided navigation through the Azure OpenAI Studio interface.
  • Deployment and management strategies for Large Language Models (LLMs).

Integrating AI Models into Applications

  • Leveraging the Playground feature for comprehensive model testing.
  • Model access and deployment via Postman and Python APIs.
  • Familiarization with ChatGPT and essential Prompt Engineering techniques.

Advanced AI Techniques

  • Process for fine-tuning AI models to address specialized tasks.
  • Image generation capabilities using DALL-E studio.
  • Comprehension and deployment of text embeddings.
  • Advanced Prompt Engineering methods for optimizing model interaction.

AI Model Combinations

  • Creating robust applications by combining text, image, and audio models.
  • Audio transcription and text generation using Whisper AI.

Securing and Optimizing AI Implementations

  • Implementing robust security protocols for AI-driven chatbots.
  • Utilizing content filters to ensure data integrity and safety.

Project: AI-Powered Solutions Development

  • Architecting a web application that leverages Azure OpenAI models.
  • Synthesizing diverse AI functionalities into a unified system.

Requirements

  • A foundational understanding of cloud computing platforms.
  • Proficiency in Python programming.
  • No previous experience in AI is necessary to participate.

Target Audience

  • AI developers seeking to expand their toolset.
  • Enthusiasts interested in exploring AI technologies.
 14 Hours

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