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How to Learn Python: A Beginner's Guide for Getting Started with Python Programming

4 October 2023

How to Learn Python: A Beginner's Guide for Getting Started with Python Programming

Introduction to Python

Python is a high-level, general-purpose programming language that emphasizes code readability and speed of development. Created in 1991 by developer Guido van Rossum, Python has a clear, logical syntax that is easy for beginners to pick up yet powerful enough for experienced programmers. This guide will help you get started. If you are serious about Python you should consider training in one of our Python training courses listed at the end of this article. 

Some of the key features and benefits of the Python language include:

  • Easy to read and understand: Python code is designed to be readable and resembles everyday English, with clear formatting and indentation. This makes it highly accessible for Python beginners.
  • Versatile and cross-platform: Python can run on various operating systems like Windows, Linux and Mac OS, and can be used to build a wide range of applications from simple command-line programs to large web applications.
  • Vast libraries and frameworks: Python has a comprehensive standard library plus a huge selection of third-party packages covering everything from data analysis to web development. Popular frameworks like Django and Flask facilitate building robust applications.
  • Supportive Python community: As an open-source language, Python has an active global community that provides excellent learning resources and documentation for users of all skill levels.

With Python in high demand across many industries, it's a great time to start learning Python programming. The hands-on skills you gain will open up opportunities to build your own applications and analyze data, or pursue Python careers like web developer, data analyst, automation specialist, machine learning engineer and more.

Setting Up Your Python Environment

Before you can start running Python programs and scripts, you need to set up your Python programming environment. This involves installing the Python interpreter on your operating system, and installing code editors and IDEs (Integrated Development Environments) to write your Python code.

Install Python Interpreter

To execute Python code, you need the Python interpreter (also called the Python execution environment) installed. Follow these steps to install Python:

  • Go to the official Python website and download the latest stable release. Make sure to pick the Python 3 version.
  • Run the installer executable file and follow the setup wizard. Make sure to check the box that adds Python to your system PATH.
  • Open the command prompt or terminal on your operating system and type python --version to verify that Python is installed correctly.

You should see the installed Python version printed out.

Set Up Python Code Editor or IDE

While you can write Python code using a simple text editor, using a customized code editor or IDE provides a more streamlined workflow. Here are some top options:

  • PyCharm: Robust IDE with intelligent code assistance and debugging tools
  • Visual Studio Code: Lightweight, customizable editor with Python support
  • Atom: Hackable text editor with features for writing and running code
  • Jupyter Notebook: Web-based notebook environment for data analysis and visualization
  • IDLE: Python's built-in IDE that comes with the standard distribution

Download and install your preferred Python code editor. For example, you can install VS Code, then install the Python extension to add Python language support.

Virtual Environments and Package Managers

It's recommended to isolate your Python projects in separate virtual environments, rather than installing packages globally. This prevents version conflicts between different projects. Python comes with the venv module to create virtual environments and the pip package installer.

To create a virtual environment called myenv:

python -m venv myenv

Activate the environment:


Install packages within that environment using pip install, such as:

pip install pandas

Other popular package/environment managers like Conda and Poetry also exist.

With your Python programming environment now set up, it's time to start learning the basics of the Python language.

Learning Python Basics

Python is a relatively straightforward language to learn, especially if you have some programming experience. We'll cover fundamental Python concepts including data structures, statements and functions.

Key Data Types

Like any programming language, Python has built-in data types that are used to define variables and data structures. The main data types include:

  • Integers - Whole numbers like 1, 5, 100
  • Floats - Decimal numbers like 1.5, 5.0, 100.75
  • Strings - Ordered sequences of characters defined in quotes like "Hello"
  • Lists - Ordered collections of objects in square brackets like [1, 2, 3]
  • Tuples - Immutable ordered sequences like (1, 2, 3)
  • Dictionaries - Unordered key-value pairs like {"name": "John", "age": 25}

Here's an example assigning these data types to variables:

number = 10 #integer
price = 24.99 #float 
name = "John" #string
items = ["Spam", "Eggs", "Beans"] #list
point = (10, 20) #tuple
person = {"name":"Mary", "age":23} #dictionary

Variables and Operators

  • Variables store values and can be assigned with = like num = 10
  • Expressions use operators like +, -, *, / to generate new values
  • Comparisons use operators like ==, !=, >, < to evaluate conditions


total = num + 10 # Addition  
diff = 20 - 10 # Subtraction
product =  5 * 2 # Multiplication
quotient = 100 / 20 # Division

flag = num > 10 # Greater than
is_equal = total == 20 # Equality check

Control Flow Statements

Python uses typical control flow statements similar to other languages:

  • if, elif, else statements for conditional branching
  • for loops for iterating over sequences
  • while loops for repeating execution until condition changes


# If statement  
if score >= 90:
  print("A grade")
elif score >= 80:
  print("B grade")  
  print("No grade")
# For loop   
for num in [1, 2, 3, 4, 5]:
# While loop
count = 0
while count < 5:
  count += 1


Functions group code blocks for reuse and organize programs into logical modules. Functions are defined with def and called to execute the logic. Parameters allow passing data into functions.

# Function definition
def double(x):
  return x * 2

# Call function  
print(double(3)) # Returns 6 

Python has many built-in functions like print(), len(), range() etc. You can also import functions from Python modules.

Classes and Objects

Python supports object-oriented programming (OOP) with classes and objects. A class defines attributes and behaviors while an object is an instance created from the class.

# Class definition
class Person:
    def __init__(self, name, age): = name
        self.age = age

# Create object     
person = Person("Mark", 23)

print( # Prints name attribute  
print(person.age) # Prints age attribute

With this solid grounding of Python basics including key data structures, operators, control flow, functions and OOP, you can write simple Python scripts. Next let's level up your skills with some intermediate concepts.

Mastering Intermediate Python

Once you grasp Python basics, you can move on to more advanced Python programming concepts that will take your code to the next level:

List and Dictionary Comprehensions

Comprehensions provide an elegant way to create lists and dictionaries using a compact syntax.

values = [x*2 for x in range(10)] # List comprehension
squares = {x: x*x for x in range(5)} # Dictionary comprehension 

Lambda Functions

These anonymous, inline functions are defined with lambda for simple one-line expressions.

double = lambda x: x * 2
print(double(7)) # Prints 14

Built-in Modules

Python ships with many standard libraries and modules like math, random, statistics, collections, datetime etc.

import math
print(math.factorial(6)) # Prints 720

from datetime import date  
print( # Prints today's date

Working with Files and Exceptions

  • The open() function opens files and try/ except blocks handle exceptions.
# Open file
f = open("test.txt", "r") 

  num = int(input("Enter a number: "))
  print(100 / num)  
except ZeroDivisionError:
  print("Cannot divide by zero")   

Debugging Python Code

  • Use print() statements to inspect variables.
  • Set breakpoints and step through code in an IDE like PyCharm.
  • Improve code quality with linting tools like Pylint and Flake8.

With this knowledge of intermediate skills like comprehensions, built-in modules and debugging, you can write more powerful Python programs. Next let's explore some specific domains where Python excels.

Python for Data Analysis and Visualization

One of Python's most popular uses is data analysis thanks to its powerful libraries like Pandas, NumPy and Matplotlib.

NumPy for Numerical Data

The NumPy library adds support for large, multi-dimensional arrays and matrices along with mathematical and statistical functions to operate on them.

import numpy as np

arr = np.array([1, 2, 3])
print(arr + 2) # Adds 2 to each array element 

NumPy is great for performing complex matrix operations.

Pandas for Data Analysis

The Pandas library provides easy-to-use data structures and data analysis tools for loading, analyzing and manipulating datasets.

import pandas as pd

df = pd.DataFrame(data)
df.sort_values("Name") # Sorts table by Name column

Pandas makes importing, managing and analyzing tabular data much simpler.

Matplotlib for Visualizations

Matplotlib is the most popular Python library for producing charts, graphs and plots to visualize data.

import matplotlib.pyplot as plt

plt.plot(x_data, y_data) # Displays plot  

The Matplotlib visualizations like histograms, scatterplots, and bar charts help uncover insights from data.

Python's specialized libraries like Pandas, NumPy and Matplotlib are indispensable for doing meaningful data analysis and visualizations to derive actionable insights from data.

Python Web Development

Another common use case for Python is building web applications and websites, for which Python has fantastic web frameworks.

Flask vs Django

The most popular Python web frameworks are Django and Flask.

  • Django is a batteries-included framework providing an ORM, admin interface and more out of the box. It enforces structure and conventions.
  • Flask is a lightweight framework offering more flexibility. It has fewer assumptions about project structure.

Building Web Apps

Key steps for building web applications in Python include:

  • Setting up the project structure
  • Creating routes and views to handle requests
  • Integrating with databases like SQLite or MySQL
  • Rendering HTML templates for content
  • Handling forms and user input

For example, a simple Flask app:

from flask import Flask
app = Flask(__name__)

def index():
    return "<h1>Hello World!</h1>"
if __name__ == "__main__":

This powerful yet simple template displays "Hello World!" at the website route.

Python enables building full-featured websites and web apps quickly with its web application frameworks.

Where to Go From Here?

You should now have a solid base of Python knowledge to start writing your own scripts and programs. Here are some recommendations for advancing your Python skills:

  • Take online Python courses on platforms like Coursera, Udemy and edX to continue building your skills.
  • Work through coding exercises on sites like HackerRank, LeetCode and Codecademy to practice Python.
  • Build your own projects like a web scraper, a productivity script or a data analysis program.
  • Contribute to open source Python projects on GitHub.
  • Join Python meetup groups and the Python Discord server to engage with the community.
  • Consider getting certified through exams like PCAP (Certified Associate in Python Programming) offered by the PSI.

Python has seen immense growth in popularity and usage over the last decades. With this comprehensive guide, you now have an excellent foundation to launch your journey as a Python developer to expand your programming skills.

So go forth and build something awesome with Python!

Frequently Asked Questions

Q: Is Python worth learning in 2023?

A: Absolutely - with growing demand across many industries, Python remains one of the top programming languages to learn in 2023 and beyond. The versatility, large community and abundance of resources make Python a great investment.

Q: What can I build with Python skills?

A: Some examples of what you can build with Python include web applications and sites, desktop GUI apps, data analysis and visualizations, machine learning models, web 

Q: What can I build with Python skills?

A: Some examples of what you can build with Python include web applications and sites, desktop GUI apps, data analysis and visualizations, machine learning models, web scraping scripts, automation bots, and more. Python is incredibly versatile.

Q: Is Python easy for beginners to learn?

A: Yes - Python strikes an excellent balance between being simple for beginners yet also powerful for experienced programmers. The clean syntax, indentation structure and focus on readability make Python highly accessible for new programmers.

Q: Should I learn Python 2 or Python 3?

A: You should learn Python 3, which is the latest and recommended version. Python 2 is legacy and no longer supported. All modern Python courses and resources use Python 3.

Q: What IDE is best for Python programming?

A: Some top Python IDEs include PyCharm, Visual Studio Code, Jupyter Notebook and Spyder. Try out a few options to determine the best Python IDE for your needs and preferences.

We have Python courses for every area of your teams training or can design a bespoke course to meet your companies requirements

  • Python "World Class" Rated course - A comprehensive introduction to Python - a simple and popular language widely used for rapid application development, testing and data analytics
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  • Advanced Python Mastery Achieve expert-level Python proficiency through JBI's Advanced Python Mastery training.
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  • Seminar - Python, Data Analytics & AI to gain a competitive edge Stay competitive by advancing your Python, data and AI skills with JBI's informative seminar.

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