What are the best online coding challenges to improve your Python skills for Operations Research?

1 Basics of Python

Before you begin tackling OR-specific coding challenges, you should make sure you have a strong understanding of the fundamentals of Python. Python is a high-level, interpreted, and dynamic language that has a straightforward and attractive syntax. It accommodates multiple paradigms, such as object-oriented, functional, and procedural programming as well as a wide range of built-in data structures and libraries for various tasks. To master the basics of Python, some great online coding challenges are Codecademy, HackerRank, and Codewars. Codecademy offers interactive lessons and projects on topics like variables, data types, control flow, functions, classes, modules, and more. HackerRank hosts coding contests and challenges on algorithms, data structures, mathematics, and more with a dedicated Python domain that covers basic to advanced concepts. Codewars allows you to practice and improve your coding skills by solving problems (called kata) of different levels and categories with a Python section that includes strings, lists, dictionaries, sets, tuples, loops, comprehensions, generators, decorators, and more.

2 OR Tools and Libraries

Once you have a good command of the Python language, you can start exploring the tools and libraries designed for OR applications. These provide functions and classes to help model, analyze, and solve various OR problems, such as linear programming, integer programming, network optimization, scheduling, simulation, and more. To learn and use these tools and libraries, you can try some online coding challenges. Google OR-Tools is a software suite that offers a range of OR tools and algorithms for solving optimization problems. It has a Python interface that allows you to define and solve problems using objects and methods. Pyomo is a Python-based modeling language that enables you to formulate and solve abstract and concrete optimization problems. PuLP is a Python library that provides a high-level interface for modeling and solving linear and mixed-integer programming problems. All three integrate with various solvers, such as GLPK, IPOPT, CPLEX, Gurobi, GLOP, SCIP, CBC, etc.

3 OR Problems and Case Studies

Finally, you can apply your Python and OR skills to real-world problems and case studies. These can help you understand the context, objectives, and constraints of different OR scenarios, such as transportation, logistics, manufacturing, health care, and more. Additionally, they can challenge you to develop and implement effective and efficient solutions using Python and OR tools and libraries. If you want to practice and improve your OR problem-solving skills, there are several online coding challenges available. For example, Coursera has a course called "Python and Statistics for Financial Analysis" that teaches how to use Python and OR tools to solve financial problems. DataCamp has a project called "Scheduling Crop Production" that teaches how to use Python and PuLP to optimize the production plan of a farm. Kaggle also hosts data science and machine learning competitions and challenges on various topics, such as the "Santa's Workshop Tour 2019" competition which challenges you to use Python and OR tools to optimize Santa's schedule.