Introduction:
Embark on a foundational journey into the world of artificial intelligence with our introductory course, “Generative AI Prompt Engineering Fundamentals with ChatGPT”. This course is designed to provide participants with a comprehensive understanding of generative AI, focusing on fundamental tools such as ChatGPT and Gemini.
Throughout the course, participants will delve into the functionalities and applications of generative AI tools, gaining practical knowledge about how these tools are used across various domains. They will explore the transformative impact of generative AI on society, businesses, and daily life, considering both the opportunities and challenges presented by this technology.
In addition to learning about generative AI tools, participants will examine the broader implications of AI, including ethical considerations and potential risks. Through real-world examples and case studies, they will gain insight into how generative AI is being implemented in different industries and sectors.
By the end of the course, participants will have developed a solid foundation in generative AI fundamentals, acquired practical knowledge about generative AI tools such as ChatGPT and GeminiAI, and cultivated a nuanced understanding of the broader impact and ethical considerations surrounding AI. Whether you’re a beginner curious about AI or a professional seeking to enhance your understanding of this transformative technology, “Generative AI: Prompt Engineering” offers a comprehensive introduction to the world of artificial intelligence.
Course Outline:
| Module | Title | Sections |
|---|---|---|
| 1 | Introduction to Generative AI | ◦ Overview of generative AI and its applications ◦ Understanding the difference between generative and discriminative models ◦ Key concepts such as generative models, probability distributions, and sampling techniques ◦ Deep dive into popular generative models such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Autoregressive models ◦ Discussion on the historical context and evolution of generative AI techniques ◦ Exploration of real-world applications including natural language generation, image synthesis, and music composition |
| 2 | Prompt Engineering Concepts | ◦ What is prompt engineering and its significance in generative AI ◦ Exploring the role of prompts in guiding AI models ◦ Understanding prompt format and structure ◦ Hands-on exercises on crafting effective prompts ◦ Examination of different types of prompts including single-turn, multi-turn, and conditional prompts ◦ Strategies for tailoring prompts to specific tasks or domains ◦ Case studies showcasing the impact of well-designed prompts on model performance and output quality |
| 3 | Techniques and Approaches | ◦ Interview pattern approach: Utilizing conversational prompts to generate text ◦ Chain of thought pattern approach: Constructing prompts to guide the generation of coherent narratives ◦ Exploration of other pattern approaches such as question-answer patterns, analogy-based prompts, and sentiment-based prompts ◦ Analysis of the strengths and limitations of each approach in different scenarios ◦ Practical examples and case studies demonstrating the effectiveness of each approach across various domains including storytelling, content creation, and customer support ◦ Activities encouraging participants to brainstorm and develop their own prompt-based techniques |
| 4 | Text to Image Prompt Techniques | ◦ Overview of text-to-image generation in generative AI ◦ Techniques for generating images from textual prompts ◦ Understanding the challenges and limitations of text-to-image generation ◦ Hands-on exercises on creating text-to-image prompts and interpreting the generated images ◦ Exploration of different architectures for text-to-image generation including AttnGAN, DALL-E, and CLIP-guided generation ◦ Discussion on the potential applications of text-to-image generation in fields such as design, virtual reality, and e-commerce ◦ Ethical considerations specific to text-to-image generation including issues related to intellectual property, privacy, and misinformation |
| 5 | AI Ethics | ◦ Introduction to AI ethics and its relevance in generative AI ◦ Ethical considerations in prompt engineering and generative AI applications ◦ Addressing biases and fairness in AI models generated through prompt engineering ◦ Discussion on the responsible use of generative AI in various domains ◦ Examination of real-world case studies highlighting ethical dilemmas and controversies surrounding generative AI technologies ◦ Strategies for promoting transparency, accountability, and inclusivity in the development and deployment of generative AI systems ◦ Interactive discussions and group activities encouraging participants to reflect on their own ethical frameworks and decision-making processes when working with AI technologies |
- Online course (free)
- 8 hours including video lectures, readings and exercises
