Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

Mathematical Background: We expect that the student is comfortable with basic mathematics at the level of a U.S. first-year college STEM student. This includes basic notions such as sets and functions ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

Computers can be used to help solve problems. However, before a problem can be tackled, it must first be understood. Computational thinking helps us to solve problems. Designing, creating and refining ...

This course is available on the MSc in Applicable Mathematics, MSc in Management Science (Operational Research), MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics ...

Picat is a new logic-based programming language. In many ways, Picat is similar to Prolog, especially B-Prolog, but it has functions in addition to predicates, pattern-matching instead of unification ...

This is a preview. Log in through your library . Abstract A unifying framework is developed to facilitate the understanding of most known computational approaches to integer programming. A number of ...

This is a preview. Log in through your library . Abstract In an earlier paper [20] combinatorial programming procedures were presented for solving a class of integer programming problems in which all ...