Introduction to Data Structures and Algorithms in Python

Catalog description

This course is an introduction to data types and algorithm design in computational analysis, specifically using Python. It has two main parts: The first part focuses on data structures and includes topics such as files, expressions, strings, lists, arrays, control flow, functions, object-oriented programming, and computation complexity and efficiency. This part aims to provide students with a solid understanding of general data structures in computer science and introduce key concepts for computational purposes. The second part covers algorithm design in Python and includes topics like searching trees, sorting, graph algorithms, random walks, Monte Carlo simulation, sampling, confidence intervals, and machine learning. This part emphasizes algorithm design, particularly in statistical programming. While the class prioritizes computation implementation over statistical theories and research projects, students will gain computational skills and practical experience in simulations and statistical modeling using Python programming.