| Ok, so in summary(just if anyone else needs anything from this), these are the links: 1) Emphasize completing courses/books before 11th grade. 2) Focus on projects rather than numerous courses. 3) Watch 3blue1brown's series on linear algebra, calculus, and deep learning. 4) Recommended resources include Free Code Camp, CS50, How to Design Programs, and
Nand2Tetris. 5) Stress the importance of mathematics in AI/ML and suggest studying probability,
calculus, and linear algebra. 6) Encourage the individual to start with simple projects and gradually tackle
more ambitious ones. 7) Suggest writing a complete, original application with documentation to
understand code organization. 8) Advise joining projects, looking for internships, and exploring open-source
contributions. 9) Recommend Francois Chollet's book on AI and learning TensorFlow and Keras. 10)Encourage learning practical aspects of ML/AI, such as data partitioning and
avoiding overfitting. 11)Suggest building something personally interesting or cloning an existing
project. 12)Emphasize the importance of soft skills and understanding the human side of technology. |