Master
2023/2024
Python Basic
Type:
Compulsory course (Master of Data Science)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
1 year, 1 module
Mode of studies:
distance learning
Online hours:
52
Open to:
students of one campus
Instructors:
Yury Sanochkin
Master’s programme:
Магистр по наукам о данных (о)
Language:
English
ECTS credits:
3
Contact hours:
10
Course Syllabus
Abstract
Python is a general-purpose, multi-paradigm, open-source, scripting language. It has a clean syntax with high-level data types and a powerful set of libraries. It is a simple language for beginners to learn, though it is powerful enough for writing large applications. It has been one of the most popular programming languages of recent years and has many areas of application from web applications to machine learning and data science. This 6-week course is an introduction to the Python programming language. The average time to complete this course depends on your background, but in principle, you might spend 5 to 10 hours per week.
Learning Objectives
- To complete the course, students are supposed to have mathematical skills at the high school level. Students’ academic performance is evaluated using programming assignments and project assignments. After taking this course, students should be able to: - use Python interactively; - understand interpreter and compilers; - execute a Python script at the shell prompt; - see a demonstration of IDE’s: IDLE, IPython, IPython Notebook; - use Python data types and logical expressions; - use string literals, string type, and regular expressions; - understand the difference between mutable and immutable types; - use Python statements (if...else if...else, for, while); - build flowcharts to understand the structure of the code; - understand assignment semantics; - write and call a simple function.
Expected Learning Outcomes
- Utilize basic functions and keywords to display data and perform arithmetic operations
- Write the first simple program
- Build complex branching scripts utilizing if, else, and else-if statements
- Identify and correct common errors when using loops.
- Use lists and tuples to store, reference, and manipulate data
- Manipulate strings using indexing, slicing, and formatting
- Define and call functions utilizing parameters and return data.
Course Contents
- General Introduction to Python Programming
- Python Control Structures: Selection Statements
- Python Control Structures: Iteration Statements
- Data Structures in Python
- String Data Properties and Methods
- Methods and Functions
Assessment Elements
- Programming AssignmentsWeekly programming assignments.
- SGA Ticket Aggregator
- SGA Metrics for site
- Final project
Interim Assessment
- 2023/2024 1st module0.4 * Final project + 0.3 * Programming Assignments + 0.15 * SGA Metrics for site + 0.15 * SGA Ticket Aggregator
Bibliography
Recommended Core Bibliography
- 9781785284571 - Romano, Fabrizio - Learning Python - 2015 - Packt Publishing - http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1133614 - nlebk - 1133614
- Álvaro Scrivano. (2019). Coding with Python. Minneapolis: Lerner Publications ™. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1947372
Recommended Additional 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
- Ben Stephenson. (2019). The Python Workbook : A Brief Introduction with Exercises and Solutions (Vol. 2nd ed. 2019). Springer.