US$17
weeklyor US$68 for 4 classes
使用 Python 和 Google Colab 進行人工智慧藝術
由 2 位學習者完成
年齡 10-15
現場團體小班課程
平均評分：
5.0
評論數量：(29 評論)
即時視訊會議
每週1次，共 4 週
1-8 名學習者(每班)
50 分鐘
包含什麼
4 現場會議
3 小時 20 分鐘 上課時間我們無法翻譯此文，請刷新頁面並再試一次。
課堂經歷
CONTENT: This class will consist of four meetings. In each class we will be creating AI Art using a different Python Colab Notebook. Each class will highlight different aspects of AI Art but also of tech in general. Some of these include Python, Colab, Google Drive, Github, and APIs STRUCTURE: Each class starts out with questions and/or sharing. After that the new topic is introduced and the motivation/theory is laid out. Students will then load/run their notebooks and start creating images using the new tools. After some sharing, the class ends with a demonstration using more advanced tools from various websites and different software. STYLE: I base my teaching on the Socratic method. I encourage play and exploration and prefer suggesting options to giving overt direction. I believe motivation is key in learning and I have a very strong belief in AI Art as a great tool for teaching tech. INTERACTION: This class is highly interactive. Students will get to see each other's work and ask questions but most of the interaction is with the instructor.
學習目標
Students will learn how to create AI Art with code, how to run experiments and mass produce images, and will see AI Art as part of games.教學大綱
4 課程
超過 4 週課 1:
Intro To AI Art: the Prompt
What are diffusion models and how do they work? After a brief explanation about what these generative AIs are trying to accomplish and how they are trained, we will dive into Google Colab and set up our notebooks. We will learn about Python libraries, prompting, art terms, open source, and Stable Diffusion. I will demonstrate Midjourney and we will make art in both Colab and Dreamstudio. 50 分鐘線上直播課
課 2:
Models and Parameters
What is transfer learning and how can we use it to leverage the work of the community? We'll dive in to fine-tuned models that specialize on things like Pixar, Disney, Photography, and much more. We will learn how to change image size, computation steps, and the creativity scale. We will connect to Google Drive so that our images can be automatically organized into portfolios. i will demonstrate Leonardo.ai's real time capabilities and show fine-tuned models. 50 分鐘線上直播課
課 3:
Creativity and Randomness
What is the role of AI as a creative partner? How can chance and randomness help us create art? We will learn methods for enhancing prompts such as wildcards and ChatGPT. We will learn about GitHub and use it to access files containing various types of art terms used for our prompts. We will also access prompt templates and create a MadLibs style game activity. I will demonstrate image refinement techniques in Dreamstudio and Leonardo: img2img, Controlnet, and inpainting/outpainting. 50 分鐘線上直播課
課 4:
Refining the Image
What's next? In this final installment we will dive into img2img and reveal it simple underpinnings. We will experiment with inpainting and masks. We will experiment with some amazing prompts and I will showcase some creative workflows using Comfyui. Finally, I will demonstrate the power of API's and how to use them with DALLE-3, Leonardo, and Dreamstudio. 50 分鐘線上直播課
其他詳情
父母的引導和規範
AI Art very often creates distorted images which can include deformed people and animals. Though our Colab notebooks have filters, these are not 100% effective. If students continually try to make inappropriate images, some may well appear.
先決條件
You need to have a gmail account that has access to Google Drive. The guardian's account will suffice as we are simply saving pictures temporarily. Programming experience is desirable but not required. A love of art and AI is a must!
供應清單
This course will require an unrestricted gmail account capable of accessing Google Drive and Google Colab.
外部資源
除了 Outschool 教室外，本課程也使用：
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