Price: $2,999.00

Length: 3 Days
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This Python coding bootcamp is designed for individuals with light programming experience. Data scientists and engineers will find this Python course useful as it goes over all the fundamentals of mathematical computing using Python programming language.

Who Should Attend

This course is designed for individuals of all backgrounds including:

  • Data scientists
  • Web developers
  • Entry level software engineers
  • Senior level software engineers

Objectives

At the completion of this course, students should be able to:

  • Get Python up and running
  • Create and run basic Python programs
  • Understand the fundamental concepts of coding
  • Understand the basics of data structures and control flow
  • Write elegant, reusable, and efficient code
  • Understand when to use the functional or the object oriented programming approach
  • Create reliable software by using unit tests
  • Parse XML and JSON feeds
  • Understand numpy and sympy
  • Understand Django framework
  • Understand how to be look up Python libraries and examples

Outline

Introduction to Python

  • About
  • Portability & Coherence
  • Python Drawbacks
  • Who is using Python today?
  • Python Setup
  • Python Object and Data Structure Basics
  • Python Comparison Operators
  • Python Statements
  • Methods and Functions
  • Object Oriented Programming
  • Modules and Packages
  • Errors and Exceptions Handling
  • Python Decorators
  • Python Generators
  • Advanced Python Objects and Data Structures

Setting up the environment

  • Installing Python
  • Setting up the Python interpreter
  • Creating a virtual environment
  • Python console
  • Running Python scripts
  • Python interactive shell
  • Python as a service
  • Python as a GUI application
  • Python code organization
  • Python's execution model
  • Coding guidelines

Data Types

  • Object Oriented Programming
  • Numbers
  • Immutable sequences
  • Mutable sequences
  • Set types
  • Mapping types – dictionaries
  • The collections module
  • Final considerations

Iterating and Making Decisions

  • Conditional programming
  • Looping
  • Putting this all together
  • A quick peek at the itertools module

Functions, the Building Blocks of Code

  • Why use functions?
  • Scopes and name resolution
  • Return values
  • A few useful tips
  • Recursive functions
  • Anonymous functions
  • Function attributes
  • Built-in functions

Time and Memory

  • map, zip, and filter
  • Comprehensions
  • Generators
  • Performance basics
  • Name localization
  • Generation behavior in built-ins

Advanced Python Concepts

  • OOP, Decorators, and Iterators
  • Decorators
  • Object-oriented programming
  • Custom iterator

Testing, Profiling, and Dealing with Exceptions

  • Testing your application
  • Test-driven development
  • Exceptions
  • Profiling Python
  • When to profile?

The Edges – GUIs and Scripts

  • First approach – scripting
  • Second approach – a GUI application

Data Science

  • IPython and Jupyter notebook
  • Dealing with data

The Django web framework

  • Django design philosophy
  • The model layer
  • The view layer
  • The template layer
  • The Django URL dispatcher
  • Regular expressions
  • A regex website

Debugging and Troubleshooting

  • Debugging techniques
  • Debugging with print
  • Debugging with a custom function
  • Inspecting the traceback
  • Using the Python debugger
  • Inspecting log files
  • Other techniques
  • Troubleshooting guidelines

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