Advanced Python 3 (3 Day Course) Training

We offer private customized training for groups of 3 or more attendees.

Course Description

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; working with regular expressions; working with databases, CSV files, JSON and XML; writing object-oriented code; testing and debugging; and learning about Unicode and text encoding. This advanced Python course is taught using Python 3, however, differences between Python 2 and Python 3 are noted.
Course Length: 3 Days
Course Tuition: $1190 (US)


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. Exposure to HTML, XML, JSON, and SQL would be useful.

Course Outline

IPython Notebook
Getting Started with IPython Notebook
Exercise 1: Creating Your First IPython notebook
Exercise 2: More Experimenting with IPython Notebook
Getting the Class Files
Magic Commands
Directory Commands
Command History
Last Three Inputs and Outputs
Environment Variables
Loading and Running Code from Files
Shell Execution
More Magic Commands
Getting Help
Advanced Python Concepts.....
Advanced List Comprehensions
Quick Review of Basic List Comprehensions
Multiple for Loops
Exercise 3: Rolling Five Dice
Collections Module
Named Tuples
Default Dictionaries (defaultdict)
Exercise 4: Creating a defaultdict
Exercise 5: Creating a Counter
Mapping and Filtering
Map (function, iterable)
Filter (function, iterable)
Lambda Functions
Using Lambda Functions with map() and filter()
Mutable and Immutable Built-in Objects
Strings are Immutable
Lists are Mutable
Sorting Lists in Place
The sorted() Function
Exercise 6: Converting list.sort() to sorted(iterable)
Sorting Sequences of Sequences
Sorting Sequences of Dictionaries
Unpacking Sequences in Function Calls
Exercise 7: Converting a String to a Object
Modules and Packages
Search Path for Modules and Packages
Regular Expressions
Regular Expression Syntax
Try it
Python's Handling of Regular Expressions
Working with Data
Relational Databases
PEP 0249 -- Python Database API Specification v2.0
Returning Dictionaries instead of Tuples
Exercise 8: Querying a SQLite Database
Passing Parameters
SQLite Database in Memory
Executing Multiple Queries at Once
Exercise 9: Inserting File Data into a Database
Reading from a CSV File
Finding Data in a CSV File
Exercise 10: Comparing Data in a CSV File
Creating a New CSV File
CSV Dialects
Getting Data from the Web
The Requests Package
Beautiful Soup
Exercise 11: Requests and Beautiful Soup
Classes and Objects
Classes vs. Objects
Everything Is an Object
Creating Custom Classes
Attributes and Methods
Exercise 12: Adding a roll() Method to Die
Private Attributes
Exercise 13: Properties
Objects that Track their Own History
Documenting Classes
Using docstrings
Exercise 14: Documenting the Die Class
Overriding a Class Method
Extending a Class
Exercise 15: Extending the Die Class
Extending a Class Method
Exercise 16: Extending the roll() Method
Static Methods
Class Attributes and Methods
Class Attributes
Class Methods
You Must Consider Subclasses
Abstract Classes and Methods
Understanding Decorators
Testing and Debugging
Testing for Performance
The timeit Module
The unittest Module
Unittest Test Files
Exercise 17: Fixing Functions
Special unittest.TestCase Methods
Assert Methods
Unicode and Encoding
Bits and Bytes
Hexadecimal Numbers
Exercise 18: Converting Numbers between Number Systems
hex(), bin(), ord(), chr(), and int()
Encoding Text
Encoding and Decoding Files in Python
Converting a File from cp1252 to UTF-8
Exercise 19: Finding Confusables

Course Directory [training on all levels]

Upcoming Classes
Gain insight and ideas from students with different perspectives and experiences.

Python Programming Uses & Stats

Python Programming is Used For:
Web Development Video Games Desktop GUI's Software Development
Year Created
Easy to Learn:
The learning curve is very mild and the language is versatile and fast to develop.
Massive Libraries:
You can find a library for basically anything: from web development, through game development, to machine learning.
Do More with Less Code:
You can build prototypes and test out  ideas much quicker in Python than in other language

Speed Limitations:

It is an interpretive language and therefore much slower than compiled languages.

Problems with Threading:

Multi-threaded CPU-bound programs may be slower than single-threaded ones do to the Global Interpreter Lock (GIL) that allows only one thread to execute at a time.

Weak on Mobile:

Although, there are a number or libraries that provide a way to develop for both Android and iOS using Python currently Android and iOS don’t support Python as an official programming language.

Python Programming Job Market
Average Salary
Job Count
Top Job Locations

New York City

Mountain View

San Francisco

Complimentary Skills to have along with Python Programming
The potential for career growth, whether you are new to the industry or plan to expand your current skills, depends upon your interests:
  - For knowledge in building in PC or windows, phone apps or you are looking your future in Microsoft learn C#
  - For android apps and also cross platform apps then learn Java
  - If you are an Apple-holic and want to build iOS and MAC apps and then choose Objective C or Swift
  - Interested in game development? C++
  - Data mining or statistics then go with R programming or MATLAB
  - Building an operating systems? C

Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.