This course on Deep Learning covers the basics of neural networks and their applications in AI tasks. It is essential in today’s academic and industrial settings. The course progresses from simple concepts to more complex ones, providing hands-on experience with PyTorch. Homework includes Autolab and Kaggle components, allowing students to explore different architectures and improve models continuously. The course requires knowledge of Python3, calculus, linear algebra, and probability. Grading is based on quizzes, homework, and a final project. Attendance is mandatory. The course emphasizes collaboration through study groups. Adherence to academic integrity is crucial, with severe penalties for violations.
https://deeplearning.cs.cmu.edu/./S25/index.html