My request: Please give me a plan to self-study the field of artificial intelligence. Tailor it to a person who has a degree in the humanities and very limited knowledge of math.

ChatGPT(GPT-4):
To develop a solid foundation in artificial intelligence (AI), it's essential to first learn some basics in mathematics, programming, and computer science. Since you have a humanities background and limited knowledge in math, the following plan is tailored to help you build the necessary skills gradually:

1. Mathematics fundamentals:
    a. Khan Academy: Study their courses on algebra, geometry, trigonometry, and probability.
    b. Coursera: Take the "Introduction to Calculus" course to get a basic understanding of calculus.

2. Learn programming:
    a. Codecademy: Start with Python, as it's a widely used programming language in AI.
    b. Automate the Boring Stuff with Python: Work through this book to apply your new Python skills to practical tasks.

3. Introduction to computer science:
    a. Coursera: Take the "CS50: Introduction to Computer Science" course from Harvard University.
    b. MIT OpenCourseWare: Complete the "Introduction to Algorithms" course to strengthen your problem-solving skills.

4. Machine learning basics:
    a. Coursera: Enroll in the "Machine Learning" course by Andrew Ng to get a comprehensive introduction to machine learning.
    b. Python Machine Learning (book): Read through this book to learn how to apply machine learning techniques using Python libraries.

5. Deep learning foundations:
    a. Coursera: Complete the "Deep Learning Specialization" by Andrew Ng to learn about deep learning techniques and neural networks.
    b. Fast.ai: Work through their "Practical Deep Learning for Coders" course to gain hands-on experience with deep learning.

6. Reinforcement learning:
    a. Coursera: Take the "Reinforcement Learning Specialization" offered by the University of Alberta to learn the fundamentals of reinforcement learning.

7. AI ethics and philosophy:
    a. Coursera: Enroll in the "AI Ethics" course from Duke University.
    b. Books: Read "Superintelligence" by Nick Bostrom and "Human Compatible" by Stuart Russell to explore the philosophical aspects of AI.

8. Specialize in a subfield:
    After developing a solid understanding of AI, explore specific subfields, such as natural language processing, computer vision, or robotics, and take relevant courses or join projects to further your expertise.

9. Stay updated:
    Regularly read AI-related blogs, articles, and research papers to stay informed about the latest advancements in the field. Subscribe to newsletters, podcasts, and attend conferences or workshops if possible.

10. Work on projects:
    Apply your knowledge by working on personal projects, collaborating with others, or contributing to open-source AI projects. This hands-on experience will help you build a portfolio showcasing your skills.

Remember, learning AI is a long-term process. Stay persistent, practice regularly, and seek support from online communities and forums whenever needed. Good luck!