The Data Science with Python course empowers you to excel in Python programming.

In this course, you’ll delve into data science, data analysis, data visualization, data wrangling, feature engineering, and statistics. Upon finishing the course, you’ll excel in using essential data science tools with Python.

Data science combines statistical analysis, programming skills, and domain expertise to extract insights and knowledge from data. It has become essential to various industries, from healthcare to finance, enabling organizations to make data-driven decisions.

One of the most common uses for Python is in its ability to create and manage data structures quickly — Pandas, for instance, offers a plethora of tools to manipulate, analyze, and even represent data structures and complex datasets.

Topics in Data Science from TCCI:

-Why Python is Important For Data Science?

-Benefits to learn python

– Basic Python

-Getting Started with Python:

-Why Python?

-Python installation

-Python Interpreter

-Variables in Python

-Comments in Python

-Python Keywords

Python Operators:

-Arithmetic Operators

-Relational Operators

-Logical Operators

-Bitwise Operators

-Assignment Operators

-shorthand assignment operator

-increment and decrement operator

Identity Operators and Membership Operators

Python Data Types:

-Numbers

Int()

float()

complex()

-character
-String

-String Slicing

-String lower() and upper() methods

-Various String methods

-String Concatenation

-String Format()

-Booleans Data Types

-Type Conversion in Python

input() method in Python

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Conditional Statement in Python:

if & else

Nested if

else if

-Loops in Python:

for Loop

while loops

range()

Continue

Break

Nested Loop

-Data structure in Python:
-Python Data Structures

-Lists

-List Slicing

Tuples
Sets
Dictionary
Reading and writing files with Python:

-File handling with Python

-Reading data from text-file

-Writing data to text-file

-JSON with Python

Functions in Python:
                -Create functions in Python

-Python Built-in Functions
-Object-Oriented Programming (OOPs) :

-Introduction of OOPs

-Python OOPs Concepts

-Python Classes and Objects

-Encapsulation in Python

-Class Instance Attributes in Python

-Python Class Members

-Class method vs Static method

-Python Inheritance

-Types of Inheritance Python

-Inheritance, examples of object, issubclass and super

-Polymorphism in Python

-Abstract Classes in Python

Exception Handling:

Data Science with python

– Why data science with python

-Benefits

-Python Decorators

-Python Libraries for Data Analysis

-Numpy Tutorial

-Pandas Tutorial

-Data Wrangling

-scikit Tutorial

-Statsmodel Tutorial

-Python Libraries for Data Visualization:

-Matplotlib Tutorial

-Seaborn Tutorial

-Plotly Tutorial

-histograms

Course Duration: Daily/2 Days/3 Days/4 Days

Class Mode: Theory With Practical

Learn Training: At student’s Convenience