Course Outline
Foundations of Generative AI and Azure OpenAI
- Overview of the current AI landscape and Generative AI trends.
- Introduction to the Azure OpenAI service suite.
- Initial setup of Azure accounts and OpenAI services.
Utilizing Azure OpenAI Studio and Playground
- Guided navigation through Azure OpenAI Studio.
- Interactive experimentation with various models in the Playground.
- Assessing model capabilities and recognizing their limitations.
Java Integration with OpenAI
- Configuration of the Java development environment.
- Connecting to Azure OpenAI via Java.
- Development and testing of AI features within Java projects.
- Overview of ChatGPT and its Java integration patterns.
- Application of Prompt Engineering methodologies.
AI Model Deployment in Web Applications
- Creation of Java-based web applications.
- Incorporating AI capabilities into web interfaces.
- Best practices for deployment strategies and scalability.
Image Creation with DALL-E
- Introduction to DALL-E and generative image concepts.
- Producing visual content using DALL-E Studio.
- Automating image generation through Java code.
Semantic Search via Text Embeddings
- Conceptual understanding of text embeddings.
- Implementing embedding models within Java applications.
- Development of semantic search capabilities.
Audio Processing with Whisper AI
- Fundamentals of AI-driven audio processing.
- Leveraging Whisper AI for speech-to-text conversion.
- Managing audio translation and multilingual compatibility.
Advanced AI Integration Strategies
- Synthesizing text and audio model functionalities.
- Customizing AI interactions using user data.
- Implementing keyword-based and vector search techniques.
- Refining user experiences through ChatGPT and advanced Prompt Engineering.
Security Measures and Model Fine-Tuning
- Protecting AI-enabled applications.
- Adapting models for specific business use cases.
- Ensuring output quality through content filtering.
Practical Implementation Sessions
- Live-lab exercises focused on real-world scenarios.
- Group projects and peer evaluation exercises.
- Final capstone project: Developing a comprehensive AI-powered Java application.
Course Wrap-Up and Future Directions
Requirements
- Solid proficiency in Java programming.
- Practical experience with RESTful APIs and web services.
- A strong working knowledge of cloud computing fundamentals.
Target Audience
- Java developers.
- Software engineers.
- Cloud technology professionals and enthusiasts.
Testimonials (3)
Comprehensiveness about the backround; how to do a prompt.
Olaf Kannt - Helios Klinikum Krefeld
Course - Generative AI and Prompt Engineering in Healthcare
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
