Python Training

0 Enrolled

7 hours 30 minutes

By Geeks Analytics in Data Science & Business Intelligence

About Course

Python Training

This self-paced Python training course is designed for learners who prefer flexibility without compromising on quality. Whether you’re a complete beginner or someone looking to upskill, this course allows you to learn Python programming at your own pace, anytime and anywhere. The course covers fundamental to advanced Python concepts, including data types, control structures, functions, modules, object-oriented programming, and popular libraries used in data analysis and automation.

With a rich mix of video tutorials, interactive quizzes, and hands-on coding exercises, learners can reinforce their understanding and build real-world skills. This course empowers you to master Python on your schedule, making it ideal for working professionals, students, or anyone balancing learning with other commitments.

Key Features Provided by Geeks Analytics:

On-Demand Learning: Access high-quality video lectures and course materials anytime, anywhere.
Comprehensive Curriculum: Learn everything from basics to advanced topics with clear, structured content.
Hands-On Exercises: Practice coding through quizzes, assignments, and real-world projects.
Flexible Access: Compatible with multiple devices, so you can learn on desktop, tablet, or mobile.
Lifetime Access: Revisit course content anytime for refresher or advanced learning.
Certification: Earn a certificate of completion to validate your skills.
Expert Support: Dedicated support team available for doubt resolution via forums and chat.
Community Engagement: Connect with fellow learners to share knowledge and stay motivated.

Understand the basics of Python programming language and its syntax.
Work with Python data types like strings, lists, tuples, dictionaries, and sets.
Implement control flow using loops and conditional statements.
Write reusable code with functions and modules.
Apply object-oriented programming concepts in Python.
Handle files and perform data input/output operations.
Use Python libraries such as NumPy and Pandas for data manipulation.
Perform data analysis and visualization with Python tools.
Automate repetitive tasks and scripts using Python.
Debug and troubleshoot Python code effectively.
Develop simple projects to apply Python skills in real-world scenarios.
Prepare for Python programming job roles with practical coding exercises.

Beginners and Freshers who want to start a career in programming or data science.
Working Professionals looking to upskill or switch to Python-based roles.
Students and Graduates from any discipline aiming to add programming to their skill set.
Data Analysts and Excel Users wanting to automate workflows and handle large datasets efficiently.
Software Developers interested in adding Python to their programming toolkit.
Automation Engineers and Testers exploring Python for scripting and process automation.
Entrepreneurs and Business Analysts who want to work with data and build prototypes.
Freelancers and Hobbyists looking to create small tools, apps, or automate everyday tasks.
Anyone Curious About Coding who wants a flexible, beginner-friendly path into tech.

Course Content

Section 1: Introduction and Setup

Lesson 1: What is Python? Introduction to Python’s History, Uses, and More.

12:48
Lesson 2: Installing & Setting up Python, Virtual Environment and Packages.

15:01
Lesson 3: Understanding Python Programming & Syntax.

12:10
Lesson 4: Variables and Data Types in Python

09:26
Lesson 5: Basic Input and Output in Python

12:22

Section 2: Data Structures, Operators and Control Flow

Lesson 6: Strings Operations & Slicing

15:28
Lesson 7: Lists & Tuples in Python

19:15
Lesson 8: Sets and Dictionaries in Python

14:01
Lesson 9: Exploring Common Python Functions

09:46
Lesson 10: Conditional Statements (Making Decisions in Code)

13:45
Lesson 11: Introduction to Loops (For Loop)

20:39
Lesson 12: While Loop Concept and Loops with Conditions

11:13
Lesson 13: Loop Control (Break, Continue, Else, Enumerate and Zip)

11:17
Lesson 14: Operators in Python

18:35
Lesson 15: Comprehensions (Writing Concise Loops)

13:20

Section 3: Functions and Modules

Section 4: File I/O & Exception Handling

Section 5: Object-Oriented Programming (OOP)

Lesson 28: Introduction to Object-Oriented Programming

09:03
Lesson 29: Defining Classes and Creating Objects

12:38
Lesson 30: Instance Methods and Class Variables

10:40
Lesson 31: Encapsulation & Access Control

07:46
Lesson 32: Inheritance and Sub-Classes

09:52
Lesson 33: Polymorphism

06:26
Lesson 34: Abstract Classes and Interfaces

07:16
Lesson 35: Applying OOP Concepts

20:41

Section 6: Iterators, Generators & Advanced Functions

Capstone Project

Instructors

Geeks Analytics

1 Student

5 Courses

Level All Levels
Duration 7 hours 30 minutes
Last Updated February 8, 2026
Certificate Certificate of completion

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Python Training

About Course

Python Training

Key Features Provided by Geeks Analytics:

What Will You Learn?

Material Includes

Requirements

Audience

Course Content

Section 1: Introduction and Setup

Lesson 1: What is Python? Introduction to Python’s History, Uses, and More.

Lesson 2: Installing & Setting up Python, Virtual Environment and Packages.

Lesson 3: Understanding Python Programming & Syntax.

Lesson 4: Variables and Data Types in Python

Lesson 5: Basic Input and Output in Python

Section 2: Data Structures, Operators and Control Flow

Lesson 6: Strings Operations & Slicing

Lesson 7: Lists & Tuples in Python

Lesson 8: Sets and Dictionaries in Python

Lesson 9: Exploring Common Python Functions

Lesson 10: Conditional Statements (Making Decisions in Code)

Lesson 11: Introduction to Loops (For Loop)

Lesson 12: While Loop Concept and Loops with Conditions

Lesson 13: Loop Control (Break, Continue, Else, Enumerate and Zip)

Lesson 14: Operators in Python

Lesson 15: Comprehensions (Writing Concise Loops)

Section 3: Functions and Modules

Lesson 16: Functions, Parameters, Return Values and Default Parameters

Lesson 17: Types of Function Argruments in Python

Lesson 18: Local versus Global Scope in Python

Lesson 19: Lambda and Functional Tools

Lesson 20: Modules and Packages

Lesson 21: Standard Library Modules

Section 4: File I/O & Exception Handling

Lesson 22: Working with Files (r, w, a, r+ modes) and File Paths.

Lesson 23: File Reading Techniques

Lesson 24: Writing and Appending to Files

Lesson 25: Working with CSV and JSON

Lesson 26: Introduction to Exceptions

Lesson 27: Exception Handling Best Practices

Section 5: Object-Oriented Programming (OOP)

Lesson 28: Introduction to Object-Oriented Programming

Lesson 29: Defining Classes and Creating Objects

Lesson 30: Instance Methods and Class Variables

Lesson 31: Encapsulation & Access Control

Lesson 32: Inheritance and Sub-Classes

Lesson 33: Polymorphism

Lesson 34: Abstract Classes and Interfaces

Lesson 35: Applying OOP Concepts

Section 6: Iterators, Generators & Advanced Functions

Lesson 36: Iterators and Iterables in Python

Lesson 37: Generators and Yield

Lesson 38: Decorators and Argparse in Python

Lesson 39: Type Hints and Pydantic in Python

Lesson 40: Multithreading and Multiprocessing

Capstone Project

Project Detail

Instructors

Geeks Analytics

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