We have compiled a list of valuable resources to learn about generative AI, covering various aspects from foundational concepts to practical applications.
A repository with updates on generative AI research, interview resources, and practical notebooks for hands-on learning.
A curated list of resources including video tutorials, blog posts, and hands-on courses on various generative AI topics.
Provides detailed steps for mastering generative AI, focusing on popular models like Transformers and GPT, and includes advanced techniques like fine-tuning and deployment.
Taught by Andrew Ng, the cofounder of Google Brain and an adjunct professor at Stanford University, the course explains what generative AI is and how it works, describes common use cases, and details what the technology can and cannot do.
Offers a structured path for learning AI, with interactive courses ranging from beginner to advanced levels, and emphasizes hands-on projects.
Explores the latest techniques, tools, and trends in generative AI, with applications in creative fields like marketing and design.
Includes materials on basic and stable diffusion models, fine-tuning, and practical applications in image generation.
Reviews various AI courses, including those offered by Google Cloud and IBM via Coursera, highlighting their content, pros, and cons.
This guide provides information about Generative AI tools and their use in and outside of the classroom including, the pitfalls and possibilities of AI, using Generative AI, AI in the classroom, how to cite AI, and Generative AI tools.
This research guide provides a brief introduction to generative AI platforms that highlights resources and discusses their usefulness in legal research, education, and practice, as well as the challenges and drawbacks to their use.