2022/2023
Введение в информатику и объектно-ориентированное программирование: язык Python
Статус:
Маго-лего
Кто читает:
Департамент социологии
Когда читается:
1 модуль
Онлайн-часы:
16
Охват аудитории:
для всех кампусов НИУ ВШЭ
Преподаватели:
Митрофанова Екатерина Сергеевна
Язык:
английский
Кредиты:
4
Контактные часы:
6
Course Syllabus
Abstract
This course was written with the intention of introducing beginners to the wonders of the world of Computer Science! The course assumes no prerequisite knowledge, and we hope that, by the end of the course, you will have learned how to think computationally, how to write programs in Python, and how to design classes using the principles of Object-Oriented Programming (OOP).This course utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. You will encounter STOP and Think questions that will help you reflect on the material, Exercise Breaks that will test your knowledge and understanding of the concepts discussed, and Code Challenges that will allow you to actually implement some of the concepts we will cover.
Learning Objectives
- You will encounter STOP and Think questions that will help you reflect on the material, Exercise Breaks that will test your knowledge and understanding of the concepts discussed, and Code Challenges that will allow you to actually implement some of the concepts we will cover.
Expected Learning Outcomes
- - Be able to code simple algorithms using Python
- - Find solutions to optimization problems using Python
- - Use Python to solve simple analytical tasks
- • Learn to explore and analyze data with Python.
Course Contents
- Introduction to Programming
- Variables. Strings. Printing
- Operators and Precedence. Comments
Bibliography
Recommended Core Bibliography
- 9781491962992 - Bengfort, Benjamin; Bilbro, Rebecca; Ojeda, Tony - Applied Text Analysis with Python : Enabling Language-Aware Data Products with Machine Learning - 2018 - O'Reilly Media - https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1827695 - nlebk - 1827695
- Learning Python : [covers Python 2.5], Lutz, M., 2008
- Programming Python : [covers Python 2.5], Lutz, M., 2006
Recommended Additional Bibliography
- A Tutorial on Machine Learning and Data Science Tools with Python. (2017). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.E5F82B62
- Derivatives analytics with Python : data analysis, models, simulation, calibration and hedging, Hilpisch, Y. J., 2015
- Diogo R. Ferreira. (2017). A Primer on Process Mining : Practical Skills with Python and Graphviz. Springer.
- H, S. (2013). A Byte of Python. Place of publication not identified: H, Swaroop. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsotl&AN=edsotl.OTLid0000581