Advanced Python 3.x

Short course

Inhouse

£ 201-500

Description

  • Type

    Short course

  • Level

    Advanced

  • Methodology

    Inhouse

  • Duration

    2 Days

  • Start date

    Different dates available

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, JSONand XML. This advanced Python course is taught using Python 3, however, differences between Python 2 and Python 3 are noted.

Facilities

Location

Start date

Inhouse

Start date

Different dates availableEnrolment now open

About this course

Students wanting to further their knowledge of Python Programming.

Basic Python programming experience. In particular, you should be very comfortablewith: 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.

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

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Reviews

This centre's achievements

2018

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 6 years

Subjects

  • XML training
  • Testing
  • XML
  • Big Data
  • Data Analytics
  • Data science
  • Advanced Python
  • Python 3.x
  • Python for scientists
  • Raspberry pie

Teachers and trainers (1)

Bright  Solutions

Bright Solutions

Trainer

Course programme


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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

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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

Advanced Python 3.x

£ 201-500