Python

Python

Code with a simple programming language that reads like kindergarten math, yet easily leads to lucrative jobs in research, software development, data science – Machine learning, Data Mining, big Data (Hadoop), statistics, Data visualization, data analytics.

>>>>>>>Maximize Success<<<<<<<

Python

What This Course Offers

This course is designed for the beginner, who do not have any experience at all with programming or development in order to learn how to program with Python. Topics include installing Python, data types and creating variables, input and output, decision making and repetition, iterators, list comprehension, functions, object oriented programming, inheritance, exception handling and using data structures.

Who Should Attend

• Project Managers
• Developers
• Analytics Professionals
• Anyone from any domain as no hard core programming knowledge is required
• Professionals who wish to switch to IT
• Those who had tried learning another programming language in the past and wish to restart with something simpler
• Wish to upgrade their skills
• wish to eventually steer their learning towards a related field

What You Get

• Course material
• Robust portfolio of programs to guide you at work
• Homework
• Assignments
• Projects
• Certificate of completion
• Portfolio reviews
• Resume support
• Mock interviews
• Career coaching

Duration

20 Hours (minimum)

Leaning Modes

• Classroom
• Online
• One on one private classes

Schedule

New session starts soon. Call 470-336-3966 or email contact@redbeartechnologies.com for details

Syllabus

Introduction

• What is Python
• Use cases
• Timeline
• Features
• Versions
• Distributions

Environment

• Installing Python for Mac
• Installing Python for Windows
• Setting path
• Documentation
• Help
• Command line shell, editors & IDEs
• Hello World
• Basic syntax
• Running Python script on Windows
• Running Python script on Unix

Getting Started

• Keywords
• Data Types
• Static vs Dynamic data types
• Fundamental Data Types
• Collection Types
• Mutable vs immutable objects
• Number Systems
• Variables
• Naming Conventions
• Print(), Type(), Id() functions
• Input() & raw_input functions
• Type Conversion functions
• Del keyword

Strings

• Definition
• Single quote Strings
• String indexing
• String slicing
• String functions
• String methods
• String multiplication
• String concatenation

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Operators

• Arithmetic Operators
• Relational Operators
• Logical Operators
• Assignment Operators
• Short hand Assignment Operators
• Bitwise Operators
• Membership Operators
• Identity Operators
• Precedence of Operators
• Evaluating expressions

Flow Control

• About Flow Control
• Elements of Flow Control
• Block/Clause
• Conditional Statements
• simple if
• if…else
• if…elif
• Looping Statements
• while loop
• while…else
• for loop
• using range() in for loop
• working with infinite loops
• nested loops
• Break statement
• Continue statement
• Pass statement

Collections

• Introduction
• List
• Tuple
• Set
• Dict
• Indexing
• Slicing
• Functions for collections
• Methods for collections
• Iterating through a collection
• Operators for collections
• Keywords
• Nested collections
• Mathematical set operations
• Getting dictionary values
• Reading file data into a dictionary
• Counting with dictionaries
• Difference between list, tuple & set
• List, set & dictionary comprehensions
• Sorting

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Functions

• Definition
• Calling a function
• Function parameters
• Argument types
• default
• non-default
• key word
• non key word
• arbitrary
• Return statement
• Return values
• Global & local variables
• Scope of global & local variables
• Call by value
• Call by reference
• Passing collections to functions
• Lambda functions/anonymous functions
• Passing functions to function
• Filter() & map() functions

Modules

• Definition
• Types
• Import statement
• Module Aliases/renaming a module
• From…import
• Reloading a module
• Built in properties
• Dir() function
• User defined modules
• Module search path
• Command line arguments
• Pre-defined standard modules

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Packages

• Introduction
• _init_.py file
• Definition
• Importing from packages
• Defining sub packages
• Importing from sub packages

Exception Handling

• Definition
• Syntax errors
• Runtime errors
• Need for exception handling
• Predefined exceptions
• Predefined exception handling
• try, except, finally clauses
• Named except block
• Default except block
• Handling multiple exceptions
• Nested try, except, finally blocks
• User defined exceptions
• Raise, assert statements

File Handling

• Definition of file
• Opening a file
• Reading data from a file
• Writing data to a file
• Closing a file
• Methods of file object
• Replacing the content of file
• Working with dictionaries
• Handling IO exceptions

Preview Syllabus

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Hear It From Our Students

“I took the Python basics class to learn Data Science. Before taking this course I was trying to learn on my own from different online resources which I found very difficult. This course helped streamline my thoughts.” – David