Python Programming – An introduction

Start date: 23/06/2020

Duration: 3 Days

Location: Virtual delivery

Cost: €400

Programme overview

This three day course (23-25 June) is a practical introduction to Python 3.. Participants will immediately be able to use Python to complete tasks in the real world. Participants are expected to have some programming experience (in another language). The course will cover the python programming language and the syntax required to use it effectively. It will conclude by giving a brief overview of three of the many niches where python is used extensively - data science, automation and web scraping. All concepts are reinforced by informal practice during the lecture followed by graduated lab exercises.

Prerequisites

Some level of experience with at least one other programming language is desirable. This is not an Introduction to Programming course. Working/user level knowledge of an operating system such as Linux, Windows, or MacOS.

Learning Objectives

  • At the conclusion of this course, attendees will be able to:
  • Design and program python applications using PyCharm / Spyder and Jupyter environments
  • Use the main flow of control elements in python
  • Choose the appropriate variable type when required
  • Use the different collection types, including lists, tuples and dictionaries
  • Write functions and pass parameters
  • Create classes and objects
  • Read, write and parse different types of files
  • Access operating system variables and automate tasks
  • Have an understanding of the numpy and pandas modules
  • Be able to write scripts to automate simple operating system tasks
  • Be able to obtain data from the internet
  • Create graphs using matplotlib

Course outline

Python basics

The Python environment

PyCharm or Spyder environment (or other)

Variables

Keywords

Built in functions

Variable types

 

Flow Control

if and elif

Conditional expressions

Relational operators

Boolean operators

while loops

Alternate ways to exit a loop

Functions

Defining a function

Function parameters

Global variables

Variable scope

Returning values

Lists and Tuples

About sequences

Lists

Indexing and slicing

Iterating through a sequence

Functions for all sequences

Using enumerate

Operators and keywords for sequences

The xrange() function

Understanding list comprehensions

Modules and Packages

The import statement

Zipped libraries

Creating Modules

Packages

Exception handling

Exceptions

Handling exceptions with try

Handling multiple exceptions

Handling generic exceptions

Ignoring exceptions

Using else

Cleaning up with finally

re-raising exceptions

Raising a new exception

The standard exception hierarchy

Dictionaries and sets

When to use dictionaries

Creating dictionaries

Getting dictionary values

Iterating through a dictionary

Reading file data into a dictionary

Object Oriented Programming

Defining classes

Instance objects

Instance attributes

Methods

Properties

Class data

Inheritance

Pseudo-private variables

Static methods

Functional Programming

Creating functions with no side effects

Lambda expressions

Reduce

Decorators in Python

Working with files

Text file I/O

Opening a text file

The with block

Reading a text file

Writing to a text file

“Binary” (raw, or non-delimited) data

CSV files

JSON files

Python For Data Analytics

A common use for python is to perform data science and data analytics.  This module will give a brief introduction to three libraries that are commonly used by data scientists.

Introduction to numpy

Introduction to pandas

Introduction to matplotlib

Python for Automation

Python started out as a tool for automating operating system tasks. This module will do some simple examples of the sort of folder traversal and file manipulation and network connection tasks that are commonly used for

The os module

The sys module

Command line parameters

__name__

Reading and writing environment variables

Sending an email

Python for Web Scraping

Python is commonly used for taking information from the web.  This module will scrape some data from the web and use pandas and numpy to create a visualisation of the data.

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