Course topics include:
An introductory exploration of AI music generation
Improvisation and AI
AI music style transfer
AI and human musicians collaborate
AI visual art creation
- AI image fusion and innovation
AI text generation and creation
AI news reporting and deep analysis
AI creation of visual art pieces
Chapter 1: Introduction to AI Music Generation
This chapter will teach students how to use the Magenta Studio plugin to generate unique melody compositions. Students will learn to utilize AI technology to create music with personality, embarking on a journey of music creation.
Chapter 2: Improvisation and AI
This chapter will guide students in engaging in improvisational music creation with Google A.I. Duet, resulting in creative musical dialogue compositions. Students will interact with AI, sparking musical inspiration and exploring the limitless possibilities of music creativity.
Creating Sketches
Student Work: Drawing based on AI-generated sketches
Chapter 3: AI Music Style Transfer
In this chapter, students will utilize MusicVAE technology to transform original music into different styles, creating highly distinctive style transfer compositions. Students will learn to explore the diversity of music and enrich their creative styles.
Chapter 4: AI Emotional Music Composition
In this chapter, students will learn how to use MuseNet to create music based on different emotions, completing music compositions that express specific emotions. Students will learn how to utilize AI to compose music with emotional depth, conveying feelings and ideas.
Chapter 5: Collaboration between AI and Human Musicians
In the final chapter, students will use Piano Genie to create a complete music composition, showcasing the collaborative results between AI and human musicians. Students will learn to fuse their creativity with AI, achieving a new level of music creation.
Chapter 6: AI Visual Art Creation
In this chapter, students will be taught how to use DALL-E and DeepArt to generate unique visual artworks. Students will learn to utilize AI technology to create visually artistic images with personality, embarking on a journey of visual art creation.
Chapter 7: AI Image Fusion and Innovation
In this chapter, students will be guided to use Artbreeder and RunwayML for image fusion and innovation, resulting in creative visual art compositions. Students will collaborate with AI, sparking inspiration for visual art and exploring the limitless possibilities of image creativity.
Chapter 8: AI Text Generation and Creation
In this chapter, students will utilize Aphrodite and ChatGPT technologies to generate various types of textual content, creating personalized works such as articles, stories, poems, and more. Students will learn to explore the diversity of text creation and enrich their own writing styles.
Chapter 9: AI News Reporting and Deep Analysis
In this chapter, students will learn how to use ChatGPT to write news reports based on provided materials, creating news pieces that are both informative and engaging. Students will learn how to utilize AI to create news reports with depth and breadth, enhancing their communication effectiveness.
Chapter 10: AI for Visual Art Creation
In this chapter, students will use RunwayML for visual art creation. Students will learn to utilize AI technology to create unique visual artworks, exploring new possibilities in contemporary art. Students will learn to combine machine learning with visual art, bringing distinctive visual effects to their works.
Fun AI fact
What is ChatGPT and generative AI?
ChatGPT is a chatbot based on the GPT (Generative Pre-trained Transformer) model developed by OpenAI. GPT itself is a large-scale language model based on the Transformer architecture, which has been trained on a vast amount of text data through unsupervised learning, acquiring the ability to understand and generate natural language. ChatGPT utilizes the techniques of GPT and can answer user questions, engage in conversations, and generate natural language text with contextual understanding.
Generative AI is a category of AI technology based on generative models. Generative models are machine learning models that aim to learn the probability distribution of data, enabling the generation of new data with similar characteristics to the original data. Generative AI can be applied in various fields, such as image generation, speech synthesis, text generation, and more. Through generative AI, machines can create new content or simulate real-world data to fulfill the needs of different application scenarios. Language models like GPT are examples of generative AI applied in the field of natural language processing.
