Advanced Python 3 Programming - updated for 2018

Course#: BSPT1015 - Next Public Course 13-14 March

About this Course

Course Type Course Code Duration
Python BSPT1015 2 Days

In this Python training course, students already familiar with Python programming will learn advanced Python techniques such as IPython Notebook, the Collections module, mapping and filtering, lamba functions, advanced sorting, writing object-oriented code, testing and debugging, NumPy, pandas,matplotlib, regular expressions, Unicode, text encoding and working with databases, CSV files, JSON
and XML. This advanced Python course is taught using Python 3, however, differences between Python 2 and Python 3 are noted.

Why Attend this Course?

This course contains numerous hands on exercises to build your Advanced skillset.

What Makes this Course Stand Apart?

New content developed for 2017 delivery.

What you will Learn?

Audience

Students wanting to further their knowledge of Python Programming.

Prerequisites

Basic Python programming experience. In particular, you should be very comfortable
with: working with strings; working with lists, tuples and dictionaries; loops and conditionals; and writing your own functions. Experience in the following areas would be beneficial: some exposure to HTML, XML, JSON, and SQL.

Course Outline

IPython Notebook

Getting Started with IPython Notebook

Creating Your First IPython Notebook

IPython Notebook Modes

Useful Shortcut Keys

Markdown

Magic Commands

Getting Help

AdvancedPython Concepts

Advanced List Comprehensions

Collections Module

Mapping and Filtering

Lambda Functions

Advanced Sorting

Unpacking Sequences in Function Calls

Modules and Packages

Workingwith Data

Databases

CSV

Getting Data from the Web

HTML

XML

JSON

Classes and Objects

Creating Classes

Attributes, Methods and Properties

Extending Classes

Documenting Classes

Static, Class, Abstract Methods

Decorator

Testing and Debugging

CreatingSimulations

Testing for Performance

The unittest Module

NumPy

One-dimensional Arrays

Multi-dimensional Arrays

Getting Basic Information about an Array

NumPy Arrays Compared to Python Lists

Universal Functions

Modifying Parts of an Array

Adding a Row Vector to All Rows

Random Sampling

pandas

Series and DataFrames

Accessing Elements from a Series

Series Alignment

Comparing One Series with Another

Element-wise Operations

Creating a DataFrame from NumPy Array

Creating a DataFrame from Series

Creating a DataFrame from a CSVl

Getting Columns and Rows

Cleaning Data

Combining Row and Column Selection

Scalar Data: at[] and iat[]

Boolean Selection

Plotting with matplotlib

RegularExpressions

Regular Expression Syntax

Python’s Handling of Regular Expressions

Unicodeand Encoding

Encoding and Decoding Files in Python

Converting a File from cp1252 to UTF-8

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We are all technical with a wealth of Learning & Development experience so can talk you through any specific requirements or the details of one of our courses.

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