Introduction into Python

Bachelor 2020/2021

Type: Compulsory course (Information and Communication Technologies and Systems)

Area of studies: Infocommunication Technologies and Systems

Delivered by: School of Electronic Engineering

Where: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

When: 3 year, 2 module

Mode of studies: distance learning

Instructors: Igor Nazarov

Language: English

ECTS credits: 3

Contact hours: 2

Full Syllabus

Abstract

The goal of the course is to introduce students to Python Version 3.x programming using hands on instruction. It will show how to install Python and use the Spyder IDE (Integrated Development Environment) for writing and debugging programs. The approach will be to present an example followed by a small exercise where the learner tries something similar to solidify a concept. At the end of each module there will be an exercise where the student is required to write simple programs and submit them for grading. It is intended for students with little or no programming background, although students with such a background should be able to move forward at their preferred pace. https://www.coursera.org/learn/python-programming-introduction

Learning Objectives

Have • an understanding of the basic principles of Python • the skill to meaningfully develop a program Know • basic Python Syntax • basic Python Libraries • basic Python Functions Be able to • create simple programs • work with datatypes • convert datatypes

Expected Learning Outcomes

-To know the concept of functions in Python
-Be capable of using basic functions like “if” and different types of loops
-Be able to convert datatypes
-To know how to work with lists
-To know the difference between running Python programs on Mac and Windows
-Be able to work with CSV files
-Be able to use tuples and data dictionaries
-Be able to build lists of various
-Be able to sort lists -Be able to edit records and load them from CSV files

Course Contents

Week 1: Beginning to Program in Python
Introduction and first functions. Videos: • Welcome and introduction • Introduction to the Spyder IDE • Arithmetic operations • Our first functions • Creating strings and using them in print statements • The "input" statement and combining strings • Using the "if" statement • Converting strings to numbers. Using the remainder operator • Introduction to loops - the "while" loop • The "for" loop; tracking down errors Materials for self-study: • Setting up Spyder • Starting Python. Our first lecture and exercise file. • Exercises1.py -- the exercise/lecture file for this module. • Note about a minor problem with Spyder • Practice functions for debugging Python code
Week 2: Working with Lists and Importing Libraries. The Random library
Lists, datatypes, libraries, the random library. Videos: • Introduction to lists • Lists continued • Stepping through lists using loops • Introduction to datatypes • Converting datatypes • Working with lists of sublists; writing a small report • Lists continued • Introduction to libraries. The random library • More on Loops and Append Materials for self-study: • Exercises 2 -- the exercise/lecture file for this module
Week 3 Tuples, Data Dictionaries, Text and CSV Files
So far, we have one collection data type, the list. In this module we take up two more: the tuple and the data dictionary. After that we introduce reading and writing text files and give some illustrative examples. Finally, we take up reading and writing Comma Separated Value (CSV) files. Videos: • Using tuples and data dictionaries • Reading and writing files • Running Python Programs (Windows) • Installing Environments on a Mac • Running Python Programs (Mac) • Writing scripts in Python • Reading and writing CSV files Materials for self-study: • Exercises3.py - The exercise/lecture file for this module • Python files needed for this module • Text and CSV files used during this module • FAQ/Errata: Change in Spyder; Running in a Command Prompt • If python does not run, read this file
Week 4: Functional Values, Sorting, Formatting, Statistics, and a Menu Driven Database Program
In this lesson, we take up a variety of topics and give an example using much of what we've covered in the course. First, we show how functions can return values. Then we show how to build lists of various types and how to sort these lists. After that we use the statistic library to introduce basic descriptive statistics. Finally, we show how to use formatting in print statements. As a recap, we work through an application making use of what we've learned to build a menu-driven program that maintains a small database. Videos: • Long strings, random library, building and sorting lists • Descriptive statistics • Formatting print statements • Starting the database application • Displaying the records • Adding and deleting records • Editing records • Saving records to a CSV file • Loading the records from the CSV file • Running our database application as a stand-alone program Materials for self-study: • Exercises4.py -- the exercise/lecture file for this module Additional program and data files needed for this module

Assessment Elements

Final test
Oral control
The format of the exam in module 2 can be remote, offline, or mixed, depending on the situation. The information is communicated to students no later than 10 days before the session.

Interim Assessment

Interim assessment (2 module)
0.7 * Final test + 0.3 * Oral control

Bibliography

Recommended Core Bibliography

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
Baka, B. (2017). Python Data Structures and Algorithms. Birmingham, U.K.: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1528144
Hetland, M. L. (2017). Beginning Python : From Novice to Professional (Vol. Third edition). New York: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1174463

Recommended Additional Bibliography

Bhasin, H. (2019). Python Basics : A Self-Teaching Introduction. Dulles, Virginia: Mercury Learning & Information. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1991381
Bill Lubanovic. (2019). Introducing Python : Modern Computing in Simple Packages. [N.p.]: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2291494
Gries, P., Campbell, J., & Montojo, J. (2017). Practical Programming : An Introduction to Computer Science Using Python 3.6 (Vol. Third edition). [Place of publication not identified]: Pragmatic Bookshelf. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1716748
Grus, J. (2019). Data Science From Scratch : First Principles with Python (Vol. Second edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2102311

Course Syllabus