To start in neuroscience with limited computer experience, focus on building a strong foundation in key areas of mathematics, particularly graph theory, statistics, probability, linear algebra, calculus, and differential equations. These subjects are crucial for understanding computational neuroscience and its applications. Familiarity with dynamical systems is essential for modeling neurons and neural networks. For programming, Python is recommended for its accessibility and extensive libraries for mathematics, while Matlab is widely used in the field for analysis and modeling. R is standard for statistical analysis, but many professionals prefer Matlab for its versatility. A solid grasp of these mathematical concepts and programming tools will significantly enhance your understanding and capabilities in neuroscience.