This course covers the basic mathematical concepts that will be required within the scope of Digital Transformation in Industry Non-Thesis Master's Program. The course consists of three modules: probability and statistics, linear algebra and calculus for optimization. The probability and statistics module will focus on conditional probability, Bayes’ Theorem, distributions, descriptive statistics, statistical inference, forecasting, hypothesis testing, regression, and maximum likelihood estimation. The linear algebra module will focus on vectors, matrices, linear transformations, inner product, orthogonality and eigenvectors. In the calculus for optimization, local and global optimization concepts, gradient descent/accent method and Lagrange multipliers methods will be covered.