Data science with PYTHON
- Module 1: Applied Machine Learning
Statistical learning vs. Machine learning
Iteration and evaluation
Bias-Variance trade-off - Module 2: Introduction to Python
Understand the basic and Advanced Concepts of Python
Python language characteristics
Python IDLE and execution Model
PYTHON programs on UNIX and Windows platform
Python Editors and IDEs - Module 3: Python Basics
Variables
Keywords
Buit-in Funtions
Strings
Different kind of literals
Math Operations and Expressions
Writing to Screen
String Formatting
Command Line Parameters
Flow Control
- Module 4: Sequences and File Operations
Text file I/O
Opening a Text File
The with Block
Reading and writing a Text File
Lists
Tuples
Indexing and Slicing
Iterating through a Sequence
Functions for All Sequences
Using enumerate()
Operators and Keywords for Sequences
The xrange() Function
List Comprehensions
Generator Expressions
Dictionaries and Sets - Module 5: Create functions, sorting different elements and error handling techniques
Function Parameters
Global Variables
Variable Scope
Returning Values
Sorting lists, functions, collections and dictionaries.
Errors
Generic Handling and Handling Multiple Exceptions.
Raising and Re-raising Exceptions
Import Statement and Search Path Module