Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
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.
14 Hours
Testimonials (2)
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
