Course Outline
Foundations of Generative AI and Azure OpenAI
- Exploring the current AI landscape and Generative AI trends.
- An overview of Azure OpenAI service offerings.
- Initial setup of Azure accounts and OpenAI services.
Utilizing Azure OpenAI Studio and Playground
- Navigating the Azure OpenAI Studio interface.
- Conducting experiments with various models in the Playground.
- Evaluating model strengths and constraints.
Integrating OpenAI with Java Ecosystem
- Preparing the Java development environment.
- Connecting to Azure OpenAI via Java.
- Developing and validating AI features within Java projects.
- Introduction to ChatGPT and its linkage with Java.
- Applying Prompt Engineering techniques for optimal results.
Rolling Out AI Models as Web Solutions
- Architecting web applications using Java.
- Embedding AI capabilities into web interfaces.
- Strategies for deployment and scalability.
Image Synthesis via DALL-E
- Overview of DALL-E and image generation processes.
- Creating visuals using the DALL-E studio.
- Programmatic image generation through Java code.
Text Embeddings and Semantic Retrieval
- Deciphering the concept of text embeddings.
- Implementing embedding models in Java environments.
- Constructing semantic search functionalities.
Audio Handling with Whisper AI
- Fundamentals of AI-driven audio processing.
- Utilizing Whisper AI for speech recognition.
- Managing audio translation and multilingual compatibility.
Sophisticated AI Model Combining
- Merging text and audio processing models.
- Customizing AI experiences based on user data.
- Executing keyword and vector-based searches.
- Refining interactions through ChatGPT and advanced Prompt Engineering.
Security Protocols and Model Fine-Tuning
- Safeguarding AI-integrated applications.
- Fine-tuning models to address specific use cases.
- Utilizing content filters to ensure output quality.
Practical Workshops
- Hands-on labs addressing real-world scenarios.
- Team-based projects and peer evaluation sessions.
- Capstone project: Developing a comprehensive AI-driven Java application.
Recap and Future Directions
Requirements
- Solid proficiency in Java programming.
- Working knowledge of RESTful APIs and web services.
- General familiarity with cloud computing principles.
Target Audience
- Java developers.
- Software engineers.
- Professionals interested in cloud technologies.
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
