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 Duration 14 hours

Course Outline

Introduction to AI and Google Gemini

  • Defining Artificial Intelligence (AI)
  • An overview of Google Gemini AI
  • The role of Google Gemini within the broader AI ecosystem

Grasping Large Language Models (LLMs)

  • The core foundations of LLMs
  • Architectural details of Google Gemini
  • A comparison between Gemini and alternative AI models

Initiating Work with Google Gemini

  • Preparing the development environment
  • Acquiring and utilizing the API key
  • An introduction to Gemini's API and its capabilities

Interacting with Gemini Models

  • Investigating the various Gemini models
  • Choosing the optimal model for specific projects
  • Initializing the Generative Model

Practical Use Cases for Gemini AI

  • Text-to-text processing
  • Text and image-to-text functionalities
  • Developing chat applications using Gemini
  • Ethical implications and responsible AI deployment

Advanced Capabilities and Personalization

  • A detailed exploration of Gemini's advanced features
  • Tailoring responses and fine-tuning models
  • Utilizing multimodal features

Project - Creating an AI Code Companion

  • A guided process for building a basic AI chatbot
  • Embedding Gemini AI into existing applications
  • Best practices and troubleshooting techniques

Recap and Future Directions

Requirements

  • Foundational knowledge of AI concepts
  • Practical experience with APIs and cloud services
  • Proficiency in Python programming

Target Audience

  • Software Developers
  • Data Scientists
  • AI Enthusiasts

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