Large Language Models and Prompt Engineering for Text and Images

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.

• None

• Everyone who is intrested.

• Everyone who is intrested.

Course Outline

Course Introduction

Introduction to Large Language Models

• Overview of LLMs (GPT-4 and others)
• Understanding how LLMs work
• How ChatGPT was trained

Introduction to the ChatGPT Environment

• Walk through the interface
• Customize the environment
• How to use ChatGPT
• Hands-on orientation

Effective Prompt Engineering

• Basics of prompting
• Prompt engineering
• Effective prompting patterns
• Introducing new information
• Strategies for designing and iterative refinement of prompts
• Hands-on prompt engineering exercises

Advanced Prompt Engineering

• Teaching ChatGPT new things
• Helping ChatGPT to reason
• Data analysis
• Coding
• Creating personal GPTs
• Hands-on prompt engineering exercises

Text-to-Image Models (DALL-E)

• Overview of text-to-image models (DALL-E, CLIP, etc.)
• Understanding how text-to-image models work
• Historical development and technological advancements

Fundamentals of Text-to-Image Prompting

• Basic components of effective text-to-image prompts
• The relationship between text prompts and image outputs
• Hands-on exercises

Effective Prompting for Images

• Techniques for writing detailed and specific prompts
• Exploring creativity
• Leveraging style, mood, and composition in prompts
• Practical applications
• Hands-on prompt engineering exercises

Ethical Considerations and Responsible Use

• Validity of Sources
• Plagiarism
• Addressing biases and limitations

Future Trends in Generative AI

• Continuing education resources
• Next steps