Top Python Projects You Should Consider Learning

Project-oriented learning is the best way to learn to code. Python is the most in-demand language today and to help you learn it, here are some of the most important Python Projects that you can explore:

• The Hangman Game
• Graphs in Python
• CIFAR10 Using TensorFlow In Python

In this article, you will be learning how to create these Python Projects in the following sequence:

• Introduction to Python
• How do You Create a Project in Python?
• What All Projects Can We Make in Python?
• Beginner Python Projects: Hangman Game with Python
• Intermediate Python Projects: Working with Graphs in Python
• Advanced Python Projects: Machine Learning using Python
• Conclusion

It will only be fair if I give you a small introduction to Python.

Introduction To Python

Python is a high-level, object-oriented, interpreted programming language, which has garnered worldwide attention. Stack Overflow found out that 38.8% of its users mainly use Python for their projects. Python was created by a developer called Guido Van Rossum.

Python is and always has been easy to learn and master. It is very beginner-friendly and the syntax is extremely simple to read and follow through. This definitely makes us all happy and what’s amazing is that python has millions of happy learners across the globe!

According to the website’s survey, Python’s popularity surpassed that of C# in 2018 – just like it surpassed PHP in 2017. On the GitHub platform, Python surpassed Java as the second-most used programming language, with 40% more pull requests opened in 2017 than in 2016.

This makes Python certification one of the most sought-after programming certifications.

How Do You Create A Project In Python?

The answer to this question is fairly simple and straightforward. It all starts with learning the basics and all the fundamentals of Python. This is basically a measurement index to know how comfortable you are working with Python.

The next prime step involves taking a look at the basic and easy code to familiarize yourself with the syntax and the flow of logic in the code. This is a very important step and helps set a strong foundation for later on as well. You can even check out the details of successful Spark developer with the Pyspark online training. 

Python in Real Life?

After this, you should definitely look at what python is being used for in real life. This will play a major role in finding out why you want to learn Python in the first place.

If that’s not the case then you will learn about the projects and you can implement certain strategies for the projects that you will consider starting on your own.

Followed by this is definitely to look at what projects you can tackle your current knowledge of Python. Diving into the depth of Python will help you assess yourself at every stage.

Projects are basically used to solve a problem at hand. If providing solutions to various simple and complex problems is your kind of thing, then you should definitely consider working on Python projects.

After you’ve got your hands dirty with a couple of projects, you will be one step closer to mastering python. This is important because you will be able to spontaneously implement what you’ve learned on something as simple as writing a calculator program all the way to helping achieve artificial intelligence.

What All Projects Can We Make In Python?

We can segregate a list based on the skill level of the learner. Based on that the projects are classified as beginner level, intermediate and advanced projects using Python.

Beginner Level Projects in Python

• Hangman Game With Python
• Snake Game Using Pygame
• Scientific Calculator Using Python
• Product landing Page using Python Flask
• URL Shortener Using Python

Intermediate Level Projects in Python

• Web Scraping Using Python
• Exploratory Data Analysis
• Pong Game using Kivy in Python
• Login System Using Python Flask/Django Web Frameworks
• Survival Prediction on Titanic Data

Advanced Level Projects in Python

• Face Mask Detection Using OpenCV Python
• Speech Recognition Using Python
• Text To Speech Using Python
• Chatbot In Python
• Web browser Automation Using Selenium

Let’s begin by checking out the first level of Python projects.

Beginner Python Project: Hangman Game with Python

The best beginner project we can consider is the game of Hangman. I am sure the majority of you reading this Python Projects blog has played Hangman at one point of time in your life. To put it in just one single statement, the main goal here is to create a “guess the word” game. As simple as it sounds, it has certain key things you need to note. 

• The user needs to be able to input letter guesses.
• A limit should also be set on how many guesses they can use.
• Keep notifying the user of the remaining turns.

This means you’ll need a way to grab a word to use for guessing. Let us keep it simple and use a text file for the input. The text file consists of the words from which we have to guess.

You will also need functions to check if the user has actually inputted a single letter, to check if the inputted letter is in the hidden word (and if it is, how many times it appears), to print letters, and a counter variable to limit guesses.

Key Concepts to keep in mind for this Python Project:

• Random
• Variables
• Boolean
• Input and Output
• Integer
• Char
• String
• Length
• Print

Code:

1. Hangman.ipynb

NOTE: Use ctrl+click (windows) and cmd+click (mac) on the below colab logo to try out the code on your own.

Now that we saw how we can tackle a beginner project like Hangman, let us step it up a little and check out an intermediate Python Project next. 

Intermediate Python Project: Working With Graphs In Python

The best way to get started with learning intermediate stages of programming in Python is to definitely start working with the libraries that Python supports.

There is literally ‘n’ number of libraries that you can make use of while coding in Python. Some are very easy and straightforward while some might take some time to grasp and master.

Here are some of the top libraries you can consider starting out with:

• NumPy
• SciPy
• Pandas
• Matplotlib

NumPy is for scientific computing as a whole.

Scipy uses arrays like basic data structure used for linear algebra, calculus, and other similar concepts.

Pandas are used for dataframes and Matplotlib is to visualize data in the form of graphs and notations.

The best possible usage of Python is for data visualization. As helpful as numeric data output is, there are many requirements for a visual representation of the data.

By visual representation, it is just a generalization. Anything ranging from creating your front-end or a Graphical User Interface (GUI) to plotting numeric data as points on a graph.

2. Python Matplotlib 

Matplotlib is used to plot data points on a graph. And Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+. 

There are many options for doing 3D plots in Python, but here are some common and easy ways to use Matplotlib.

In general, the first step is to create 3D axes, and then plot any of the 3D graphs that best illustrate the data for a particular need. In order to use Matplotlib, the mplot3d toolkit that is included with the Matplotlib installation has to be imported:

NOTE: Use ctrl+click (windows) and cmd+click (mac) on the below colab logo to try out the code on your own.

Now that we are familiar with how we can expand our reach on learning Python by looking at external libraries, we can go ahead and check out the next level of Python Projects which is the Advanced Level.

Advanced Projects With Python

Python has vast applications – Everything from “Hello World” all the way to achieving Artificial Intelligence.

There are virtually unlimited projects you can work on using Python but here are the major ones that you can consider if you want to dive into the heart of Python.

• Machine Learning with PyTorch, TensorFlow, Keras, and whatever Machine Learning libraries you like.
• Computer vision using OpenCV and PIL.
• Creating and publishing your own pip module with tests and documentation.

Among all of these, my favorite is definitely to work on Machine Learning and Deep Learning. Let us look at a very nice use-case to learn Python in-depth.

3. Implementation Of CIFAR10 Using TensorFlow In Python

Let’s train a network to classify images from the CIFAR10 Dataset using a Convolution Neural Network built-in TensorFlow.

Consider the following Flowchart to understand the working of the use-case:

Let us break down this flowchart into simple terms:

• We first load images into our program
• These images are stored in a place where the program can access it
• We need Python to make sense of the information that is present so we do the process of normalization
• We define the foundation of the neural network 
• Defining the loss function to ensure we obtain maximum accuracy on the dataset
• Training the actual model to learn something about the data that it has seen all this while
• testing the model to analyze the accuracy and iterate through the training process to achieve better accuracy

This use-case is broken into 2 programs. One is to Train the network and the other is to test the network.

Let us explore the following colab notebook.

NOTE: Use ctrl+click (windows) and cmd+click (mac) on the below colab logo to try out the code on your own.