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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.
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