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Python Programming Course

Course Level: Beginner
Duration: 9 Hrs 24 Min
Total Videos: 33 On-demand Videos

Master Python programming in this comprehensive course designed for aspiring developers, data scientists, and tech enthusiasts. From foundational basics to advanced concepts, equip yourself with future-proof skills for a lucrative career in diverse tech sectors, guided by seasoned IT professionals.

Buy An all access pass to over 3,000 hours of training

Learning Objectives

01

Master the basics of Python programming, including the syntax and key concepts.

02

Understand and manipulate primitive data types in Python effectively.

03

Learn to efficiently handle multiple assignment statements in Python.

04

Gain the ability to convert data types in Python for diverse programming needs.

05

Create, modify, sort, reverse, and slice lists in Python to manage data.

06

Work with operators in Python and determine operator precedence for effective coding.

07

Develop proficiency in using IF statements, For loops, and While loops in Python.

08

Learn to define functions, use arguments, handle exceptions, and work with modules in Python.

Course Description

This Python Programming Course is designed for beginners and professionals alike who want to build a solid foundation and advance to real-world practice. If you’re just starting online and aiming to gain practical, job-ready skills, you’ll finish with a proven ability to apply Python in multiple domains.

In this program, you’ll move from core coding fundamentals to hands-on projects that matter in today’s tech roles. You’ll learn practical Python concepts such as loops, data types, and file handling, while also exploring how Python powers web development, data science, and machine learning. The engaging modules and flexible online learning format are built for busy schedules and real-world outcomes, guided by IT professionals who bring industry perspectives to every lesson.

Whether you’re pursuing a career in development, data science, or research, this course helps you translate theory into value. You’ll gain confidence writing clean code, building small applications, and tackling real problems with scripting and automation. The curriculum is organized to reinforce concepts with practice exercises and progressively challenging projects that align with modern tech demands.

Key topics you’ll cover include introductory Python, primitive data types, control flow with loops, file handling, and practical scripting techniques. You’ll also explore how Python fits into broader workflows in web development, data science, and machine learning, empowering you to contribute meaningfully in teams and on projects from day one.

  • Hands-on practice with Python programming fundamentals and real-world projects
  • Ability to implement Python scripts for data manipulation and automation
  • Experience building small web components or data-driven scripts for practical use
  • Confidence to apply Python skills across web development and data science contexts

Ready to advance your career with a future-proof skill set? Enroll now and start turning Python knowledge into valuable work-ready capabilities that employers recognize and reward.

Who Benefits From This Course

  • Individuals looking to start a career in software development
  • Data analysts seeking to improve their data manipulation skills
  • Students studying computer science or a related field
  • Professionals looking to switch to a career in tech
  • Researchers needing to automate data collection and analysis
  • Engineers interested in scripting and automation
  • Web developers looking to enhance their back-end development skills
  • IT professionals who want to expand their programming toolkit
  • Individuals interested in developing and automating tasks

Frequently Asked Questions

What is Python programming and why is it important?
Python is a high-level, interpreted programming language that has gained popularity due to its simplicity and readability. It is widely used in various fields including web development, data analysis, machine learning, artificial intelligence, and more. The importance of Python lies in its versatility and efficiency. It allows developers to write fewer lines of code compared to other languages, reducing complexity and improving productivity. Also, the large and active Python community contributes to an extensive selection of libraries and frameworks, making it easier to implement complex functionalities.
What job roles require Python programming skills?
There are several job roles that require Python programming skills, including but not limited to:
  • Data Scientist: They use Python for data analysis, visualization, and machine learning.
  • Software Developer/Engineer: They use Python to develop various types of software, from simple scripts to complex applications.
  • Machine Learning Engineer: They use Python for designing and implementing machine learning models.
  • Web Developer: They use Python and its frameworks (like Django or Flask) for server-side web development.
  • DevOps Engineer: They use Python for scripting and automation in the DevOps lifecycle.
How is Python used in data science?
Python is a popular language in the field of data science due to its simplicity and the wide availability of data-centric libraries. It provides libraries like Pandas for data manipulation and analysis, NumPy for numerical computation, Matplotlib, and Seaborn for data visualization, and Scikit-learn for machine learning. Python's simplicity and readability make it easy to clean, analyze, and visualize data, making it a go-to choice for many data scientists.
What is the average salary of a Python developer?
The average salary of a Python developer in the United States is approximately $117,155 per year. However, this can vary widely depending on the specific role (for example, a Data Scientist or a Machine Learning Engineer may earn more), level of experience, and the location of the job.
What are the prerequisites to learn Python programming?
Python is often recommended for beginners due to its simplicity and readability, making it a great first language. Therefore, there are no strict prerequisites to start learning Python. However, having a basic understanding of concepts like variables, loops, and functions can be beneficial. Additionally, familiarity with basic mathematics and logical reasoning can help in understanding algorithms and data analysis techniques commonly used in Python programming.

Included In This Course

Module 1: Getting Started with Python

  •    Module 1 File
  •    Intro to Course and Instructor
  •    Getting Started with Python

Module 2: Working with Primitive Data Types

  •    Module 2 File
  •    Working with Primitive Data Types
  •    Working with Primitive Data Types Part 2
  •    Working with Primitive Data Types Part 3
  •    Working with Primitive Data Types Part4
  •    Working with Primitive Data Types Part4 Answers

Module 3: Working with Multiple Assignments Statements

  •    Module 3 File
  •    Working with Multiple Assignments Statements

Module 4: Convert Types in Python

  •    Module 4 File
  •    Convert Types in Python

Module 5: Creating Lists

  •    Module 5 File
  •    Creating Lists

Module 6: Modifying Lists

  •    Module 6 Notes
  •    Modifying Lists

Module 7: Sorting and Reversing Lists

  •    Module 7 File
  •    Sorting and Reversing Lists

Module 8: Slicing Lists

  •    Module 8 File
  •    Slicing Lists

Module 9: Working With Operators

  •    Module 9 File
  •    Working With Operators
  •    Working With Operators Part2
  •    Working With Operators Part3

Module 10: Determining Operator Precedence

  •    Module 10 File
  •    Determining Operator Precedence

Module 11: Working with IF Statements

  •    Module 11 File
  •    Working with IF Statements

Module 12: Working With For Loops

  •    Module 12 File
  •    Working With For Loops

Module 13: Working With While Loops

  •    Module 13 File
  •    Working With While Loops

Module 14: Nesting for Loops

  •    Module 14 File
  •    Nesting for Loops

Module 15: Reading Files

  •    Module 15 File
  •    Reading Files Part1
  •    Reading Files Part2

Module 16: More on Files

  •    Module 16 File
  •    More on Files

Module 17: Merging Emails

  •    Module 17 File
  •    Merging Emails

Module 18: Reading Console Inputs and Formatting Outputs

  •    Module 18 File
  •    Reading Console Inputs and Formatting Outputs

Module 19: Reading Command Line Argument

  •    Module 19 File
  •    Reading Command Line Argument

Module 20: Defining Functions

  •    Module 20 File
  •    Defining Functions

Module 21: Using Default Argument

  •    Module 21 File
  •    Using Default Argument

Module 22: Using Keyword and Positional Arguments

  •    Module 22 File
  •    Using Keyword and Positional Arguments

Module 23: Handling Exceptions

  •    Module 23 File
  •    Handling Exceptions

Module 24: Using Math and Random Modules

  •    Module 24 File
  •    Using Math and Random Modules

Module 25: Displaying Daytime Working Directory and File Metadata

  •    Module 25 File
  •    Displaying Daytime Working Directory and File Metadata
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