In this course, you’ll embark on a journey to master one of the most versatile and powerful programming languages available today. We cover everything from Python’s core syntax to advanced topics like data manipulation, automation, and web development. Through hands-on projects and practical exercises, you’ll learn to write efficient code, develop robust applications, and leverage Python’s extensive libraries for data analysis and machine learning. This course is designed to help you build a strong programming foundation, enabling you to tackle a wide range of problems and drive innovation in various fields.
Beginners in Programming: If you’re new to programming, Python is a great starting point due to its simple and readable syntax.
Professionals Looking to Upskill: Many fields, from data analysis to web development, use Python. Learning it can enhance your current skill set and open up new career opportunities.
Students and Graduates: Python is widely used in scientific research, data analysis, and academic projects. It can be a valuable tool for students and researchers.
Data Scientists and Analysts: Python is a dominant language in data science and analytics due to its powerful libraries and tools. Anyone who are working or want to work in the field of Data Science And Analytics.
Pre-requisites
Curious to Learn
Willingness to Practice
Course content
IMPORTANT: Currently we are re-desiging all our courses and latest syllabus will be available as soon as it is ready.
1.Introduction to Python
What can Python do?
How to install Python
2.Python Basics
Working with Print Statement
Comments
Simple Input & Output
Simple Operations in Python
3.Working with Variables, Data Types
What is Variable
Data Types
Working with
Numbers
Booleans
Strings
Date
4.Functions, Modules & Packages in Python
Creating First Function in Python
Function Parameters
Variable Arguments
Default Arguments
Scope Of a Function
Lambda Function
Creating Modules in Python
5.Decision Making in Python
Logical Operators in Python
If-elif-else statements
6.Loops in Python
For Loop
While Loop
Nested Loop
7.Branching
Break
Continue
Pass
8.Using Array, Lists, Sets, Tuples and Dictionaries
Array
List
Sets
Tuples
Dictionaries
9.Exception handling in Python
Errors Vs Exception
Exception handing
Handling multiple exceptions
Writing your own Exception
Raising Exceptions
10.OOPs (Object Oriented Programming) in Python
Classes
Methods
Objects
Inheritance And Polymorphism
11.Working with Files & Folders
Creating Folder
Creating Multiple Folders
Deleting File
Deleting Folder
Copying Files
Copying Folders
Reading Zip
Extracting Zip
Creating Zip
Reading .txt
Writing data to .txt
Reading .CSV
Writing data .csv
12.Working with SQLite
Instructions for installing and using SQLite and its tools.
create a database and connect to it using Python
Defining schemas, creating tables, and understanding data types and constraints.
Performing CRUD Operations using Python
Managing exceptions and implementing best practices for database operations
13.Pandas
Overview of Pandas and its key features for data manipulation and analysis
Understanding and using Series and DataFrames for storing and manipulating data
Reading from and writing to various file formats (CSV, Excel, SQL, etc.)
Handling missing values, filtering, and transforming data for analysis
Performing descriptive statistics, aggregations, and data visualization
Using operations such as merging, joining, grouping, and pivoting to reshape data
Working with date and time data, and performing time series analysis and manipulation
14.NumPy
Overview of NumPy and its role in numerical computing with Python
Creating and manipulating ndarray objects, including array attributes and basic operations
Techniques for accessing and modifying array elements and subarrays
Performing element-wise operations and using NumPy’s mathematical functions
Understanding and applying broadcasting rules for operations on arrays of different shapes
Using functions to compute statistics like mean, median, variance, and sum
Performing matrix operations, including dot products, matrix multiplication, and decompositions
15.MatPlotLib
Overview of Matplotlib and its role in data visualization with Python
Creating simple plots, including line plots, scatter plots, and bar charts
Adjusting plot appearance with titles, labels, legends, and styles
Creating subplots, multiple plots, and handling multiple datasets in a single figure
Using Matplotlib for histograms, pie charts, box plots, and other advanced visualizations
Exporting plots to various formats (e.g., PNG, PDF) and customizing output resolution
Enabling interactive features and integrating with Jupyter Notebooks for dynamic visualizations
16.Projects
Snake Game
Pong Game
Web scraping
Selenium
Creating Rest API
Power BI Integration Project with Python
Hands-on learning
Real-world projects
Easy to follow lessons
Comprehensive Curriculum
Certificate of Excellence
Live online sessions
Web Developers: Python’s frameworks, like Django and Flask, are popular for web development. Anyone who wants to master python to navigate their career to web development.
Automation Experts: If you’re interested in automating repetitive tasks or processes, Python’s ease of use makes it a great choice.
Game Developers: Python can be used for game development with libraries like Pygame.
Hobbyists and DIY Enthusiasts: Whether you’re working on a personal project or a hobby that involves programming, Python’s versatility can be very helpful.