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Duration 14 hours
Course Outline
Introduction to AI and Generative AI
- Core principles of AI and its influence on technology.
- An exploration of Generative AI fundamentals and real-world applications.
Deploying the Azure OpenAI Service
- Establishing an Azure OpenAI account.
- Reviewing quotas, pricing structures, and usage policies.
Working with Azure OpenAI Studio
- Navigating the user interface of Azure OpenAI Studio.
- Deploying and managing Large Language Models (LLMs).
Integrating AI Models into Applications
- Utilizing the Playground feature for model testing.
- Accessing and deploying models using Postman and Python APIs.
- Introduction to ChatGPT and advanced Prompt Engineering techniques.
Advanced AI Techniques
- Fine-tuning AI models for specialized operational tasks.
- Generating images via the DALL-E studio.
- Understanding the mechanics and deployment of text embeddings.
- Refining Prompt Engineering skills for optimal model interaction.
Combining AI Models
- Synthesizing text, image, and audio models to build robust applications.
- Translating and generating text from audio inputs using Whisper AI.
Securing and Optimizing AI Implementations
- Implementing robust security measures for AI-driven chatbots.
- Applying content filters to ensure data integrity and compliance.
Project: Developing AI-Powered Solutions
- Designing a web application that leverages Azure OpenAI models.
- Integrating diverse AI functionalities into a unified system architecture.
Requirements
- A foundational understanding of cloud computing platforms.
- Practical experience with Python programming.
- No previous experience with AI is required.
Target Audience
- AI developers.
- Enthusiasts of AI technologies.
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