Why this course?

Description

A "Python Masterclass" typically refers to an intensive and comprehensive course designed to teach participants a broad and deep understanding of Python programming. These master classes often cover a wide range of topics, from the fundamentals to advanced concepts and best practices. The goal is to empower participants to become proficient Python developers and leverage the language for various applications.

Python is a versatile and powerful programming language that is widely used in various domains, 
including web development, data science, artificial intelligence, automation, and more. This master 
class will guide you through the fundamentals of Python and help you become proficient in writing 

The features of a Python Masterclass can vary based on the specific course content  Comprehensive Python Masterclass typically includes a range of elements designed to provide participants with a deep understanding of Python programming.

Fundamentals Reinforcement: Through coverage of fundamental concepts such as data types, loops, functions, and object-oriented programming (OOP) to establish a strong foundation. 
Data Structures and Algorithms: Coverage of essential data structures (lists, sets, dictionaries) and 
algorithms, with a focus on applying them effectively in Python.

A Python Masterclass is designed to equip participants with a deep and comprehensive understanding of the Python programming language. The skills acquired in such a master class can be applied across various domains and use cases. 

Advanced Python Programming Skills:
Master classes go beyond the basics and cover advanced topics in Python programming. Participants can deepen their understanding of the language and its features.

Data Science and Machine Learning:
Python is a popular language for data science and machine learning. A master class may cover 
libraries such as NumPy, Pandas, Matplotlib, and scikit-learn, allowing participants to work on data 
analysis and machine learning projects.
 

Network Programming:
Python is used for network programming, and a master class may cover topics like socket protocols, and building programming, network networked applications
 

Databases and SQL:
Python is often used in conjunction with databases. A master class might cover database connectivity and interaction, including working with SQL databases using libraries like SQLAlchemy.

CONCEPTS OF PYTHON MASTER CLASS:
A Python Master Class typically covers a wide range of concepts to provide participants with a thorough understanding of the Python programming language. 

Basic Python Syntax:
Covering fundamental syntax elements such as variables, data types, operators, control structures (if statements, loops), and functions.

Object-Oriented Programming (OOP):
In-depth coverage of OOP concepts like classes, objects, inheritance, polymorphism, encapsulation, and abstraction.

Exception Handling:
Understanding how to handle errors and exceptions in Python using try, except, and finally blocks.

File Handling:
Learning to work with files, including reading and writing data to text files, CSV files, and other file
formats.
 

Functional Programming:
Understanding functional programming concepts, including higher-order functions, lambda functions, and the use of map, filter, and reduce.

Data Science and Machine Learning:
Overview of libraries like NumPy, Pandas, Matplotlib, sci-kit-learn, and Jupiter Notebooks for data analysis and machine learning.

Modules of Python Master Class:

Module 1 Introduction to Python
Module 2 Python – Tools Syntaxes & Data Structures
Module 3 Python – Dictionaries, Date and Time
Module 4 Python – MySQL
Module 5 Pandas library – Introduction
Module 6 Pandas library – Data Structures
Module 7 Numpy library – Introduction
Module 8 Numpy library – Array Manipulations, Mathematical Functions
Module 9 Matplotlib, Histogram Using Matplotlib | I/O with Numpy
Module 10 Matplotlib Library - Introduction, Pyplot API | Types of Plots
Module 11 seaborn Library
Module 12 SKLearn Library
Module 13 Python – Date and Time, Data Wrangling.
Module 14 Python – Data Cleansing
Module 15 Python – Word Tokenization, Stemming and Lemmatization.
Module 16 Python – Data Visualization
Module 17 Python – Statistical Analysis
Module 18 Python – Types Of Distribution
Module 19 Python – Correlation, Chi-Square Test, Linear Regression
Module 20 Keras library – Introduction.
Module 21 Stock Price Prediction with Machine Learning LSTM RNN
Module 22 People’s behavior in chat message using NLP 
Module 23 Snake game in Python - Using Py game module
Module 24 ChatBot creation in Python NLP
Module 25 Electricity Price Prediction Using ML Random Forest Regressor
Module 26 Diamond Price Prediction Using Python Linear Regression
Module 27 Earthquake Prediction Model Neural networks
Module 28 Colour Recognition with Machine Learning OpenCV
Module 29 Titanic Survival Analysis Using ML Logistic Regression
Module 30 Block-Chain in Python