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Python Programming

 

Getting started with Python

 

• Overview of Python

• Installing Python

• Getting ready to develop

 

Python Language Fundamentals

 

• Overview of core Python syntax rules

• Simple data types and variables

• Object essentials

• Flow control

 

Working with Functions

 

• The benefit of functions

• Writing and calling functions

• Passing parameters

 

Exception Handling

 

• Overview of exceptions in Python

• Handling exceptions

• Raising exceptions

• Design issues

 

Collections

 

• Overview of collections in Python

• Lists

• Tuples

• Sets

• Dictionaries

 

Strings and Regular Expressions

 

• Overview of strings in Python

• Basic string manipulation

• Introduction to regular expressions

 

Classes and Iterators

 

• Defining classes

• Instance variables

• Iterators

• Creating and initializing objects

 

File Handling

 

• Overview of file handling in Python

• Reading and writing text files

• Binary files

• Streaming and serializing

 

XML Processing

 

• XML essentials

• Parsing XML documents

• Searching for XML content

• Generating XML data

 

Web Services

 

• Overview of Web services

• Implementing Web services using Python

• Caching

• Compression

• Handling redirects

 

Recap Essential Python Features

 

• Language Fundamentals

• Functions

• Data Structures

• Defining and Using Packages

• Additional Techniques

 

Object-Oriented Programming

 

• Essential concepts

• Defining and using a class

• Class-wide members

 

Additional Object-Oriented Techniques

 

• A closer look at attributes

• Implementing special methods

• Inheritance

 

XML Processing

 

• XML essentials

• Reading XML data in Python

• Locating content using Xpath

• Updating XML data in Python

• Using the LXML library

 

Functional Programming

 

• Functional programming in Python

• Higher order functions

• Additional Techniques

 

Web Processing

 

• Python web servers

• Python rest services

• Python web sockets

 

Decorators

 

• Getting started with decorators

• Additional decorator techniques

• Parameterized decorators

 

Asynchronous Processing in Python

 

• Getting started with asynchrony in Python

• Creating tasks to run in different threads

• Additional task techniques

 

Getting Started with Python Data Science and NumPy

 

• Introduction to Python data science

• NumPy arrays

• Manipulating array elements

• Manipulating array shape

 

NumPy Techniques

 

• NumPy universal functions

• Aggregations

• Broadcasting

• Manipulating arrays using Boolean Logic

• Additional techniques

 

Getting Started with Pandas

 

• Introduction to Pandas

• Creating a series

• Using a series

• Creating a DataFrame

• Using a DataFrame

 

Pandas Techniques

 

• Universal functions

• Merging and joining datasets

• A closer look at joins

 

Working with Time Series Data

 

• Introduction to time series data

• Indexing and plotting time series data

• Testing data for stationarity

• Making data stationary

• Forecasting time series data

• Scaling back the ARIMA results

 

Introduction to Machine Learning

 

• Machine learning concepts

• Classification

• Clustering

 

Getting Started with Scikit-Learn

 

• Scikit_Learn essentials

• A closer look at datasets

 

Understanding the Scikit-Learn API

 

• Introduction

• Scikit-Learn API essentials

• Performing linear regression

 

Going Further with Scikit-Learn

 

• Introduction

• Understanding Naive Bayes classification

• Naive Bayes example using Scikit-Learn

 

Case Study

 

• Worked example of a real-world data science problem