Course Outline

Introduction

  • Python versatility: from data analysis to web crawling

Python Data Structures and Operations

  • Integers and floats
  • Strings and bytes
  • Tuples and lists
  • Dictionaries and ordered dictionaries
  • Sets and frozen sets
  • Data frame (pandas)
  • Conversions

Object-Oriented Programming with Python

  • Inheritance
  • Polymorphism
  • Static classes
  • Static functions
  • Decorators
  • Other

Data Analysis with Pandas

  • Data cleaning
  • Using vectorized data in pandas
  • Data wrangling
  • Sorting and filtering data
  • Aggregate operations
  • Analyzing time series

Data Visualization

  • Plotting diagrams with matplotlib
  • Using matplotlib from within pandas
  • Creating quality diagrams
  • Visualizing data in Jupyter notebooks
  • Other visualization libraries in Python

Vectorizing Data in Numpy

  • Creating Numpy arrays
  • Common operations on matrices
  • Using ufuncs
  • Views and broadcasting on Numpy arrays
  • Optimizing performance by avoiding loops
  • Optimizing performance with cProfile

Processing Big Data with Python

  • Building and supporting distributed applications with Python
  • Data storage: Working with SQL and NoSQL databases
  • Distributed processing with Hadoop and Spark
  • Scaling your applications

Extending Python (and vice versa) with Other Languages

  • C#
  • Java
  • C++
  • Perl
  • Others

Python Multi-Threaded Programming

  • Modules
  • Synchronizing
  • Prioritizing

Data Serialization

  • Python object serialization with Pickle

UI Programming with Python

  • Framework options for building GUIs in Python
    • Tkinter
    • Pyqt

Python for Maintenance Scripting

  • Raising and catching exceptions correctly
  • Organizing code into modules and packages
  • Understanding symbol tables and accessing them in code
  • Picking a testing framework and applying TDD in Python

Python for the Web

  • Packages for web processing
  • Web crawling
  • Parsing HTML and XML
  • Filling web forms automatically

Summary and Next Step

Requirements

  • Beginner to intermediate programming experience
  • Knowledge of math and statistics
  • Knowledge of database concepts

Audience

  • Developers
 28 Hours

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