Description:

This specialized course invites learners to delve into the world of Large Language Models (LLMs), with a focus on ChatGPT. The course begins with a foundational overview of LLMs, explaining their workings, training processes, and the evolution of chat-based models. As the course progresses, learners are guided through the ChatGPT interface, learning to customize and effectively interact with this powerful tool through hands-on orientation. A significant emphasis is placed on prompt engineering, from foundational principles to advanced techniques. The initial part of the course focuses on text generation. For example, creative writing, summarization, and modifying or improving existing text, along with many other use cases. The course will also lay out the primary components of an effective prompt.

The latter part of the course shifts focus towards text-to-image prompting, focusing particularly on DALL-E. Participants will learn how to craft detailed prompts that guide generative AI to produce incredible images. The course covers the principles of effective prompting for image generation and strategies for refining prompts to achieve more accurate and imaginative results, offering a blend of technical understanding and creative exploration.

Duration: 2 days

Course Code: BDT331

Learning Objectives:

After completing this course, you will be able to:

• Explain the fundamentals of Large Language Models (LLMs) including GPT-4 and others.
• Navigate and customize the ChatGPT environment for various uses.
• Employ effective prompt engineering techniques to communicate with ChatGPT efficiently.
• Design and iteratively refine prompts to improve ChatGPT’s responses.
• Teach ChatGPT new information and assist it in reasoning, data analysis, and coding tasks.
• Create personalized GPT models for specific applications.
• Understand the principles of text-to-image models, including how they work.
• Develop effective text-to-image prompts that leverage style, mood, and composition for creative applications.
• Recognize ethical considerations and the importance of responsible use of AI technologies, including addressing biases and limitations.
• Identify the validity of sources and understand the implications of plagiarism in the context of generative AI.
• Be aware of future trends in generative AI.