Module 1: Python Core

Introduction of python and comparison with other programming languages
Installation of Anaconda Distribution and other python IDE
Python Objects, Numbers & Booleans, strings, Container objects, Mutability of objects
Conditions (if else , if –elif-else)
Loops (while, for)
Break and Continue Statements
Operators – Arithmetic, Bitwise, comparison and Assignment
Operators, Operators Precedence and associativity.
Range functions

Module 2: String Objects and collections

String object basics
String methods
Splitting and Joining Strings
String format functions
List object basics
List methods
List as stack and Queues
List comprehensions

Module 3: Tuples, Set, Dictionaries & Functions

Tuples, Sets, Dictionary Object basics, Dictionary
Object methods, Dictionary View Objects.
Functions basics, Parameter passing, Iterators
Generator functions
Lambda functions
Map, Reduce, filter functions

Module 4: OOPS concepts & Working with Files

OOPS basic concepts
Creating classes and Objects
Inheritance, Multiple Inheritances
Working with files
Reading and writing files
Buffered read and write
Other File methods

Module 5: Modules, Exception Handling & Database Programming

Using Standard Module
Creating new modules
Exceptions Handling with Try-except
Creating, inserting and retrieving Table
Updating and deleting the data.

Module 6: Flash and Api’s

Flask introduction
Flask Application
Open linkFlask
App RoutingFlask
HTTP MethodsFlask

Module 7: Visualisation


Module 8: Pythonpandas

Python Pandas – Series
Python Pandas -DataFrame
Python Pandas – Panel
Python Pandas – BasicFunctionality
Function Application
Python Pandas -Reindexing
Python Pandas – Iteration
Python Pandas – Sorting
Working with Text Data
Options & Customization
Indexing & Selecting Data
Statistical Functions
Python Pandas – Window Functions
Python Pandas – Date Functionality
Python Pandas –Time delta
Python Pandas – Categorical Data
Python Pandas – Visualization
Python Pandas – IOTools

Module 9 : Python Numpy

NumPy – Ndarray Object
NumPy – Data Types
NumPy – Array Attributes
NumPy – Array Creation Routines
NumPy – Array from Existing Data
Array from Numerical Ranges
NumPy – Indexing & Slicing
NumPy – Advanced Indexing
NumPy – Broadcasting
NumPy – Iterating Over Array
NumPy – Array Manipulation
NumPy – Binary Operators
NumPy – String Functions
NumPy – Mathematical Functions
NumPy – Arithmetic Operations
NumPy – Statistical Functions
Sort, Search & Counting Functions
NumPy – Byte Swapping
NumPy – Copies &Views
NumPy – Matrix Library
NumPy- Linear Algebra

Module 10: Exploratory Data Analysis

Feature Engineering and Selection
Building Tuning and Deploying Models
Analyzing Bike Sharing Trends
Analyzing Movie Reviews Sentiment
Customer Segmentation and Effective Cross Selling
Analyzing Wine Types and Quality
Analyzing Music Trends and Recommendations
Forecasting Stock and Commodity Prices

Topic :


Class Duration 45 Days

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