Oct 14, 2024, 07:48 PM IST

Mathematics for Computer Science (MIT) This course covers discrete mathematics, including logic, proofs, set theory, and combinatorics, tailored for computer science applications.

Linear Algebra (Harvard University) A comprehensive introduction to linear algebra, focusing on vector spaces, matrices, determinants, eigenvalues, and applications in data science and engineering.

Calculus: Single Variable (University of Pennsylvania) An introductory course that covers limits, derivatives, integrals, and the fundamental theorem of calculus, emphasizing problem-solving techniques.

Introduction to Probability (Harvard University) This course explores the principles of probability theory, including random variables, distributions, and applications to real-world problems.

Statistics 110: Introduction to Probability (Harvard University) A foundational course in statistics and probability that emphasizes understanding statistical reasoning and data interpretation.

Introduction to Statistics and Data Science (Columbia University) Learn the basics of statistics and data science, focusing on data analysis, visualization, and statistical inference using real-world examples.

Differential Equations (University of Pennsylvania) This course covers ordinary differential equations, including techniques for solving and applying them in various scientific fields.

This information is not DNA's opinion but obtained from media reports