The class is intended for university students in their early years, preparing for their math exams. It covers topics such as: calculus, analysis, (linear, vector, matrix) algebra, geometry, trigonometry, (basic) statistics, probability, combinatorics, business mathematics, but also more abstract topics, such as topology, measure / integration theory and functional analysis. Depending on the student's requirements, lessons may consist of: - A (comprehensive) overview of the course material, e.g. slides, lecture notes, etc. - Working out specific (types of) problems, exercises, (old) exams. - Working out homeworks / assignments. - Setting up final reports and projects.
Provides assistance with computer science modules with a strong mathematical component: predicate logic, cryptography, number theory, algorithm design, discrete / combinatorial optimization, graph theory, linear programming, machine learning, etc. Lessons consist of: - Working out specific (types of) problems, exercises, (old) exams. - Working out homeworks / assignments. - Setting up final reports and projects.
Stochastic Processes, Markov Chains, Queueing Theory, Stochastic Calculus, Stochastic Differential Equations and Applications, Risk Management. The class is intended for advanced students which are following (pre-) Master courses in one of the above listed topics.
- Provide guidance / supervision in the use of mathematical / statistical methods (estimation, regression, testing, statistical analysis, etc) in research projects (machine learning, psychology, sociology, economics, finance, risk management), with presentation / interpretation of the results in a scientifically compliant way. - Provide assistance in implementing computer code relevant for the above type of research projects. The class is suited for MSc students who need to complete their thesis, as well as for practitioners who are conducting various research studies.
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If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.
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