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Duration 14 hours
Course Outline
Module 1: Introduction to AI and Google Gemini
- An overview of Artificial Intelligence (AI)
- An introduction to Google Gemini AI and its ecosystem
- Key features and benefits of Gemini compared to other AI models
- Practical Task: Exploring Gemini AI via the Google AI Studio demo
Module 2: Understanding Large Language Models (LLMs)
- The fundamentals of large language models
- The architecture and functioning of Gemini models
- A comparison of Gemini with GPT and other leading models
- Practice Lab: Visualizing tokenization and model responses using sample prompts
Module 3: Getting Started with Gemini
- Configuring the development environment
- Interacting with the Gemini API and SDK
- Authentication, tokens, and API keys
- Hands-on Lab: Executing your first Gemini prompt using Python
Module 4: Working with Gemini Models
- Exploring various Gemini model types and their capabilities
- Choosing the right models for language, image, or multimodal tasks
- Initializing and testing generative models
- Practical Exercise: Comparing outputs from text-to-text and image-to-text models
Module 5: Practical Applications and Use Cases
- Integrating Gemini AI into chat and Q&A applications
- Building semantic search and summarization tools
- Ethical AI usage and considerations regarding bias
- Group Project: Creating a “Smart Research Assistant” using NotebookLM and Gemini
Module 6: Advanced Features and Customization
- Prompt optimization and advanced context management
- Utilizing Gemini for code generation and debugging
- Fine-tuning workflows with Google Cloud Vertex AI
- Hands-on Activity: Adjusting model responses using parameters and temperature control
Module 7: Real-World Projects and Collaboration
- Planning collaborative projects and setting up workflows
- Integrating Gemini AI with other Google tools (Drive, Docs, Sheets)
- Team Project: Designing and deploying a small AI application (e.g., content summarizer, chatbot, or idea generator)
- Peer review and discussion of project outcomes
Module 8: Evaluation and Future Directions
- Troubleshooting common issues in Gemini projects
- Reviewing the Gemini API roadmap and upcoming features
- Best practices for AI governance and scalability
- Wrap-up Activity: Reflecting on practical lessons learned and their career applications
Summary and Next Steps
Requirements
- A foundational understanding of basic AI concepts
- Familiarity with APIs and cloud services
- Experience with Python programming
Target Audience
- Developers
- Data scientists
- AI enthusiasts
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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