This project focuses on the implementation of various algorithms and the exploration of programming paradigms such as procedural, object-oriented, and event-driven programming. The project also covers ...

We are given a array of price predictions for m stocks for n consecutive days. The price of stock i for day j is A[i][j] for i = 1,…,m and j = 1,…,n. You are tasked with finding the maximum possible ...

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

Graph algorithms are integral for solving complex programming challenges. They provide methods for handling data relationships through graphs, which are essential in fields like network analysis, ...

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

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 ...

Many important practical computations, such as scheduling, combinatorial, and optimization problems, use techniques known as integer programming to find the best combination of many variables. In ...

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 ...