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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
Testimonials (1)
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