You'll Learn

Module One   

Intalling Python

• Python on Windows
• Python on Mac OS

Working with variables and data

• Naming and using variables
• Numbers, strings and boolean
• Stripping whitespaces
• Concatenating strings
• Stripping whitespaces
• Tabs and newlines
• Integers and floats
• Writing comments
• Strings manipulation

Working with Lists and Tuples

• Accessing Elements in a List
• Working with Elements (appending, adding, sorting, deleting )
• For Loop
• Looping through an entire list
• Slicing and looping through a slice
• Copying a list
• Organizing a list
• List comprehension
• Vertical summation
• Defining a tuple
• Tuples and Lists conversion
• Looping through a Tuple

If and Conditional Statements

• Various conditional tests ( equality and inequality checking )
• Conditional testing on a list
• Boolean Expressions
• if-else , if-elif-else
• Using if statement with multiple lists
• Nesting Blocks
• While Loop using a list
• While Loop using a flag
• Flow control with break statement
• Flow control with continue statement

Dictionaries

• Accessing values in a Dictionary
• Adding new key-value pairs
• Looping through all key-value pairs
• Looping through all values in a dictionary

Getting user Input

• Using input() function
• Handling numberical input

Functions

• Defining a function
• Arguments and parameters
• Working with positional arguments
• Working with keyword arguments
• Setting arguments' default values
• Returning result from a function

Working with Modules

• Storing functions in a module file
• Importing an entire module
• Importing individual functions

Using Python's standard modules

• Math module
• Datetime module
• Random module
• OS module

Working with files

• Reading data from a txt or csv files
• Merging and working data from a file
• Writing to a file

Errors handling

• Handling error using Exception
• The try-except blocks
• The else block
• Displaying errors messages

Module Two  

Data Preparation and loading

• Data loading using Pandas
• Working with problematic data
• Dealing with big datasets

Data Processing with Pandas

• Introduction to Data Structures
• Series / DataFrame / Index Objects
• Viewing and selecting data
• Statistical and histogramming operations
• String methods
• Concatenating / joining / appending data
• Arithmetic methods
• Operations between DataFrame and Series
• Function application and mapping
• Sorting and Ranking
• Doing common Excel tasks in Pandas
• Doing Pivot Table in Pandas

Data Processing with Numpy

• Array Creation - N-dimensions
• Printing Arrays
• Numpy DataTypes and conversion
• numpy.ndarray methods
• Basic arrays elementwise operations
• Matrix product using dot function
• Universal functions
• Indexing, slicing and iterating
• Shape manipulation
• Copies and views
• Data Processing Using Arrays

Data Visualization

• pyPlot Basics
• Knowing different chart elements
• Charting with Pandas
• Plotting a single interactive chart
• Saving your charts
• Subplots
• Plotting multiple charts

Machine Learning

• Supervised and unsupervised Learning
• Training set and testing set
• Dimensionality reduction
• The PCA Decomposition
• K-Nearest Neighbours Classifier
• Linear Regression
• Polynominal interpolation and curve fitting
• Support Vector Machine