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Course Outline
Module 1: Introduction to AI and Google Gemini
- What is Artificial Intelligence (AI)?
- Overview of Google Gemini AI and its ecosystem
- Key features and advantages of Gemini over other AI models
- Hands-on Activity: Exploring Gemini AI through the Google AI Studio demo
Module 2: Understanding Large Language Models (LLMs)
- Fundamentals of large language models
- The architecture and operation of Gemini models
- Comparing Gemini with GPT and other leading models
- Practice Lab: Visualizing tokenization and model responses using sample prompts
Module 3: Getting Started with Gemini
- Setting up the development environment
- Working with the Gemini API and SDK
- Authentication, tokens, and API keys
- Hands-on Lab: Running your first Gemini prompt using Python
Module 4: Working with Gemini Models
- Exploring different Gemini model types and capabilities
- Selecting appropriate models for language, image, or multimodal tasks
- Initializing and testing generative models
- Practical Exercise: Comparing text-to-text and image-to-text model outputs
Module 5: Practical Applications and Use Cases
- Integrating Gemini AI into chat and Q&A applications
- Developing semantic search and summarization tools
- Ethical AI usage and bias considerations
- Group Project: Build a “Smart Research Assistant” using NotebookLM and Gemini
Module 6: Advanced Features and Customization
- Prompt optimization and advanced context handling
- Using Gemini for code generation and debugging
- Fine-tuning workflows with Google Cloud Vertex AI
- Hands-on Activity: Customizing model responses using parameters and temperature control
Module 7: Real-World Projects and Collaboration
- Collaborative project planning and workflow setup
- Integrating Gemini AI with other Google tools (Drive, Docs, Sheets)
- Team Project: Design and deploy a small AI application (e.g., content summarizer, chatbot, or idea generator)
- Peer review and discussion of project results
Module 8: Evaluation and Future Directions
- Troubleshooting common issues in Gemini projects
- Exploring the Gemini API roadmap and upcoming features
- Best practices for AI governance and scalability
- Wrap-up Activity: Reflection on practical lessons learned and career applications
Summary and Next Steps
Requirements
- An understanding of basic AI concepts
- Experience with APIs and cloud services
- Python programming experience
Audience
- Developers
- Data scientists
- AI enthusiasts
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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