Intro to Programming in Python

2023/2024

Учебный год

ENG

Обучение ведется на английском языке

6

Кредиты

Кто читает:

Институт когнитивных нейронаук

Статус:

Курс обязательный

Когда читается:

1-й курс, 3, 4 модуль

Преподаватель

Сохраби Маджид

Course Syllabus

Abstract

Python is widely regarded as one of the easiest and most popular programming languages to learn. This course provides a solid understanding of Python’s fundamental concepts and constructs, making it an ideal choice for beginners. It serves as a foundation for tackling diverse problems, such as data analysis and software development. With a focus on data science applications, the course covers topics like data importation, storage, manipulation, and essential analysis tools. It is designed for students with limited programming experience, acting as a stepping stone to more specialized areas of Python, including machine learning, statistical data processing, and data visualization.

Learning Objectives

• By actively engaging in a significant number of practical exercises during class and at home, as well as actively participating in group projects, students consistently achieve outstanding results.
• This course aims to equip students with a solid foundation in Python by covering key concepts, syntax, functions, and packages. It focuses on writing scripts for data manipulation and analysis. The course includes topics such as variable types, operators, statements, loops, and essential data science packages like NumPy, Pandas, and Matplotlib. By the end of the course, students will have the ability to write concise scripts to import, prepare, and analyze data effectively.
• By completing the course successfully, the student can apply the knowledge in solving problems in the Cognitive Science field.

Expected Learning Outcomes

• Skill of using NumPy, SciPy, Jupyter notebooks.
• Know how to apply the existing software (MNE Python \ Brainstorm) and build pipelines for solving the inverse problem and present the results.
• Know and differentiate basic Python data types. Choose the correct data types based on the problem in hand
• Know and understand basic Python syntax
• Use Python for routine tasks automation
• Learn more details on hypothesis testing

Course Contents

• Introduction to Python. Review of the environment setup process. Anaconda IDE. NumPy, SciPy, Jupyter notebooks.
• Data types: integers and strings. Input and output. Strings formatting.
• Data types: floating-point numbers and boolean. Logical operators. Conditionals.
• Data types: lists and tuples. For loop.
• Data types: sets and dictionaries.
• Python for data science
• Brainstorm and MNE-Python software.

Assessment Elements

• Quizzes
• Exam(Project Defence)
• Homeworks

Interim Assessment

• 2023/2024 4th module
  0.5 * Exam(Project Defence) + 0.3 * Homeworks + 0.2 * Quizzes

Bibliography

Recommended Core Bibliography

• Ben Stephenson. (2019). The Python Workbook : A Brief Introduction with Exercises and Solutions (Vol. 2nd ed. 2019). Springer.
• Severance, C. (2016). Python for Everybody : Exploring Data Using Python 3. Place of publication not identified: Severance, Charles. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsotl&AN=edsotl.OTLid0000336

Recommended Additional Bibliography

• Ivan Idris - Python Data Analysis - Packt Publishing, Limited , 2014-430 - Текст электронный - https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=1826990