2024/2025
Python базовый уровень
Статус:
Маго-лего
Когда читается:
1 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
3
Course Syllabus
Abstract
The Python programming language is one of the easiest to learn and most popular programming languages. This language is a powerful data analysis tool and can improve the efficiency of almost any activity in science and industry. Using Python, you can automate routine operations and process data volumes several orders of magnitude larger than those available for manual processing or using spreadsheets. This course is aimed at developing competencies in the field of understanding code and writing your own programs. It will cover topics that are necessary for the successful development of basic Python data types and syntactic constructs.
Learning Objectives
- Mastering the basics of the Python programming language by students, sufficient to understand someone else's code and implement their own simple programs.
Expected Learning Outcomes
- -Create variables, read information into variables, access variables.
- -Work with strings, apply indexing and formatting of strings.
- -Use logical data type, comparison operators, logical operators.
- -Write your own conditional constructions.
- -Use loops to process repetitive actions, terminate the loop by condition.
- -Understand the logic of the loop.
- -Use loops to iterate through sequences.
- - Understand the logic of the loop.
- -Distinguish between mutable and immutable data types
- -Understand which methods work with them.
- -Perform operations on sets, interpret the results meaningfully.
- -Create a dictionary and add information to it, search through the dictionary.
- -Store and access data inside nested structures.
- -Sort sequences, sort dictionaries by keys and by values.
- -Write your own functions and apply them.
- -Open and create text files.
- -Read, process and analyze information from files.
Course Contents
- Working with functions.
- Working with text and table files.
- The logical data type. Conditional constructions.
- Introduction to programming. The main types of data. Creating variables. The main errors.
- The while loop. The break and continue operators. Using else in a loop.
- The for loop. Lists and tuples. The map() function
- Methods of strings and lists. Slices.
- Sets. Operations on sets. Methods of sets.
- Dictionaries. Dictionary methods. Nested data structures.
- Sorting, the sorted() function.
Assessment Elements
- QuizzesThere will be short quizzes distributed asynchronously. Each quiz will take 5-10 minutes from starting an attempt and will cover the material of the previous weeks (particularities will be communicated at least one week in advance). Question types might be a multiple-choice or a short answer.
- Seminar TasksSmall problems with code distributed asynchronously at the Smart LMS platform. The duration of tasks is usually 10-15 min from starting an attempt.
- Home AssignmentsWeekly issued home assignments at the Smart IMS platform.
- MidtermIt is conducted after studying the topic “Dictionaries” and contains tasks on the topics covered. It lasts 80 minutes and is held in Smart LMS asynchronously. Tasks are in the form of writing code. The student's assignment is checked at open and hidden tests with a penalty of 10% for each incorrect attempt. With each incorrect attempt, the penalty increases by another 10%. Navigation through the work is NOT free (closed navigation), that is, when completing a task, you cannot return to previous tasks. The examples of tasks are similar to the examples of seminar tasks. The demo version of the test is posted in the public domain no later than seven days before the activity.
- ExamThere will be a final test at the module 1 session in the end of October synchronously with online proctoring at Smart LMS. It consists of coding problems; the duration of the exam is 2 hours.
Interim Assessment
- 2024/2025 1st module0.35 * Exam + 0.15 * Home Assignments + 0.25 * Midterm + 0.1 * Quizzes + 0.15 * Seminar Tasks
Bibliography
Recommended Core Bibliography
- 9781491912140 - Vanderplas, Jacob T. - Python Data Science Handbook : Essential Tools for Working with Data - 2016 - O'Reilly Media - https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1425081 - nlebk - 1425081
Recommended Additional Bibliography
- Vanderplas, J.T. (2016). Python data science handbook: Essential tools for working with data. Sebastopol, CA: O’Reilly Media, Inc. https://proxylibrary.hse.ru:2119/login.aspx?direct=true&db=nlebk&AN=1425081.