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Course Outline
Introduction to Generative AI and Azure OpenAI
- The landscape of AI and Generative AI
- Overview of Azure OpenAI services
- Setting up an Azure account and OpenAI service
Working with Azure OpenAI Studio and Playground
- Navigating Azure OpenAI Studio
- Experimenting with models in the Playground
- Understanding model capabilities and limitations
Integrating OpenAI with Java
- Setting up the Java development environment
- Accessing Azure OpenAI using Java
- Building and testing AI features in Java applications
- Introduction to ChatGPT and its integration with Java
- Understanding and applying Prompt Engineering techniques
Deploying AI Models as Web Applications
- Creating web applications with Java
- Embedding AI functionalities in web apps
- Best practices for deployment and scaling
Image Generation with DALL-E
- Introduction to DALL-E and image generation
- Using DALL-E studio to create images
- Generating images from Java code
Text Embeddings and Semantic Search
- Understanding text embeddings
- Implementing embedding models in Java
- Building semantic search features
Voice Processing with Whisper AI
- Basics of audio processing with AI
- Using Whisper AI for speech-to-text
- Audio translation and multilingual support
Advanced AI Model Integration
- Combining text and audio models
- Personalizing AI interactions with user data
- Implementing keyword and vector search
- Enhancing interactions with ChatGPT and Prompt Engineering
Security and Fine-Tuning
- Securing AI-powered applications
- Fine-tuning models for specific use cases
- Using content filters to maintain quality
Practical Sessions
- Hands-on labs with real-world scenarios
- Collaborative projects and peer reviews
- Capstone project: Building an AI-powered Java application
Summary and Next Steps
Requirements
- An understanding of Java programming
- Experience with RESTful APIs and web services
- Familiarity with cloud computing concepts
Audience
- Java developers
- Software engineers
- Cloud enthusiasts
14 Hours