DevOps Artisan – Introduction in Python & Data Science

01. Introduction. Writing Python Programs
Installing Python
Your First Python Program

02. Variables. Numbers. Operators
Integers
Floats
Boolean Values
Bitwise Operators
String Introduction

03. Program Flow Control
If Statements
Loops ( while, for)
Break/Continue
Functions

04. Strings
String Functions
String Indexing and Slicing
String Formatting
Immutability in Python

05. Casting variables

06. Lists
List Operations
List Methods
List Slicing

07. Tuples
Tuples vs Lists
Tuples Immutability
Pattern Matching

08. Sets
Set Methods

09. Dictionaries
Creating Dictionaries
Dictionary Methods

10. File Handling
Read files
Write/Create files
Delete files
The Context Manager

11. Functions
Function Arguments
Scoping

12. Modules
Pip install
Datetime module
Os module
Sys module
Create/Use a module
Variables/Methods in modules

13. Iterators
Yield
Generators
Iterators
Lazy Evaluation

14. Intro to Object Oriented Programming
Classes
Instances
Inheritance
Polymorphism

15. Advanced OOP
Multiple inheritance
Abstract classes
Default arguments

16. Functional Programming
What is a lambda function
Define a lambda function
Map
Filter

17. Exception Handling
try…except… finally
Raising Exceptions

18. Anaconda package manager:
Virtual Envs
Modules
How to install a module using anaconda cloud

19. DataScience: Introduction to pandas 1
DataFrames
Insert
Delete
Select

20. DataScience: Introduction to pandas 2
Merging
Conditionals

21. DataScience: Introduction to NumPy
Vectors
Matrix operations
Sorting
Indexing
Broadcast

22. DataScience: Introduction to sklearn 1
Preprocess
Model Select
Pipeline

23. DataScience: Introduction to sklearn 2
Feature Selection
Metrics
One Hot Encoding

24. Matplotlib visualization / SeaBorn
2D plotting
Histograms
HeatMap

25. IPython Notebook

26. Where to go from here?