Enrolling in this AI course requires a solid foundation in programming, mathematics, and data analysis. Prospective learners should be comfortable coding in Python, including familiarity with libraries such as NumPy and pandas. A working knowledge of linear algebra, calculus, and probability theory is essential for grasping machine learning algorithms. Familiarity with data structures, algorithms, and basic statistics will accelerate understanding of model development and evaluation. While prior experience with machine learning frameworks (e.g., TensorFlow or PyTorch) is beneficial, it is not mandatory. Strong problem-solving skills, logical reasoning, and a keen interest in artificial intelligence are the prerequisites for success in this program.