UID:
almahu_9948336504402882
Format:
XV, 209 p. 18 illus.
,
online resource.
Edition:
1st ed. 2020.
ISBN:
9783030368265
Series Statement:
Textbooks on Political Analysis,
Content:
This book is intended to serve as the basis for a first course in Python programming for graduate students in political science and related fields. The book introduces core concepts of software development and computer science such as basic data structures (e.g. arrays, lists, dictionaries, trees, graphs), algorithms (e.g. sorting), and analysis of computational efficiency. It then demonstrates how to apply these concepts to the field of political science by working with structured and unstructured data, querying databases, and interacting with application programming interfaces (APIs). Students will learn how to collect, manipulate, and exploit large volumes of available data and apply them to political and social research questions. They will also learn best practices from the field of software development such as version control and object-oriented programming. Instructors will be supplied with in-class example code, suggested homework assignments (with solutions), and material for practical lab sessions.
Note:
Chapter 1. Getting Started With Python -- Chapter 2. Building Software -- Chapter 3. Object-Oriented Programming -- Chapter 4. Introduction to Algorithms -- Chapter 5. Introduction to Data Structures -- Chapter 6. Input, Output, and the Web -- Chapter 7. Application Programming Interfaces -- Chapter 8. Databases -- Chapter 9. NoSQL Databases -- Chapter 10. Introduction to Machine Learning with Python -- Chapter 11. Linear Programming -- Chapter 12. Practical Programming -- Chapter 13. Case Study: Image Processing -- Chapter 14. Case Study: Natural Language Processing -- Chapter 15. Conclusion.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9783030368258
Additional Edition:
Printed edition: ISBN 9783030368272
Additional Edition:
Printed edition: ISBN 9783030368289
Language:
English
DOI:
10.1007/978-3-030-36826-5
URL:
https://doi.org/10.1007/978-3-030-36826-5
