MATH2601: Computer Tutorials and Assignments Academic Year 2024/25 Organisation Tutorials In the tutorials, we will introduce new tools and concepts in Python, in order to use methods from numerical analysis to solve a range of mathematical problems. Assignments Computer assignments will be set fortnightly. During the Computer Practical classes on Monday, you will be able to work independently on these assignments, under the supervision of academic staff. You should submit your work by 4.pm on the Monday in the week following the week of the Practical class to receive feedback. Write your work in a Python Jupyter Notebook called xyz_N .ipynb, where xyz is your ISS username (i.e., your login) and N the number of the assignment (1, 2, 3, 4, 5), then submit it to the Assessment area for MATH2601 on the VLE. Jupyter Notebooks will naturally allow you to write a short report, i.e., to produce an analysis of your results and to comment on them. Assessments Two of the computer assignments, 3 and 5, will be assessed. They will be graded and you will get feedback on your work. The overall Computer Assessment grade counts for 30% of the MATH2601 grade and students need to achieve at least 40% on the Computer Assessments to pass the module. Chapter 1 Computational accuracy 1.1 Tutorial 1.1.1 Motivation Suppose…
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BUAN 244: Business Analytics – Summer 2025 (CRN: 21275) As of 6/20/2025 Recommended Texts 1. R for Data Science – Hadley Wickham & Garrett Grolemund, 2017. Click here to access this freely available textbook. 2. Introduction to Data Cleaning with…
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COMS 4701 Midterm Practice Exam Spring 2024 1. Consider the directed search graph shown below. S is the start state and G is the goal state. Transition costs are shown along the graph edges. Note that the transition between C and D is bidirectional. (a) For each of the search algorithms below, indicate the largest number of nodes that may possibly be expanded, not counting the goal state. Assume all algorithms conduct the goal test upon popping a node from the frontier. (Your answer may be ∞ .) Depth-first search with no reached table Depth-first search with reached table Breadth-first search with reached table (b) Suppose we run uniform-cost search on this search graph. List the order in which nodes are expanded (do not count the goal state) and give the final solution returned. Expanded nodes Returned solution (c) Suppose we currently have a heuristic function h(n) = 0 for all nodes n. Propose a change to the heuristic of a single node (indicate both node and heuristic value), such that h remains admissible and A* may expand fewer nodes than UCS. Also write out this shorter sequence of expanded nodes.…
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