Python Projects for Final Year Students [Beginner to Advanced Ideas]

3. Integration of Geolocation APIs

By utilizing geolocation APIs, the Phone Locator App allows the user to track the phone's location in real-time. It shows the area on the interactive display, and stores its location history.

Key Features

• Track phone location in real-time.
• Show location in an interactive map.
• Share location with other sources.
• Records and displays location history.
• Setting up emergency alerts or geofencing locations. 

Libraries

• GeoPy: Used for geolocation and reverse geocoding (turning coordinate into human-readable location). 
• Folium: Used for displaying interactive maps, built on top of Leaflet.js.

Source Code: https://github.com/topics/geolocation-api?l=typescript&utf8=%E2%9C%93

4. Weather App

This is a weather application that makes calls to an external weather API to get current weather information and show it to the user. The app allows displays temperature, humidity, conditions, and forecasts for upcoming days in an easy to use interface.

Key Features

• Makes a call to an API for current weather data. 
• Shows temperature, humidity, and additional details. 
• Forecasts forthe  upcoming days.

Libraries

• Requests: Used to make simple HTTP requests, and calls to an API to get weather data. 
• Tkinter: Used to create a graphical user interface with windows and widgets.

Source Code: https://github.com/PrathameshDhande22/Weather-Desktop-App

5. To-Do List App

This is a task management application that allows a user to create, edit, and delete tasks. This application has the ability to mark a task as complete; which will assist in keeping organized and managing all of one person's daily business.

Key Features

• Allow the user to add, delete, and mark tasks as complete. 
• Organizing tasks by priority or deadline.

Libraries

• Requests: Used to make simple HTTP requests and calls to an API to get weather data. 
• Tkinter: Used to create a graphical user interface with windows and widgets.

Source Code:https://github.com/Harsh456B/Python-programming-in-TO-DO-LIST

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6. Simple Chatbot

This is a basic chatbot that can reply to questions with predetermined questions with simple predicted answers. The chatbot simulates a conversation by processing user input and making relevant queries, thus showing very light, natural language processing.

Key Features

• Respond to predetermined questions with basic text responses. 
• Process user input and give relevant replies. 
• Support multiple turns of conversation.

Libraries

• NLTK: A natural language processing library for handling and analyzing text data.
• Tkinter: A toolkit for creating GUI and interacting with your applications.

Source Code: https://github.com/topics/python-chatbot

7. Simple Calculator

An easy-to-use application in which the user can perform simple arithmetic functions such as addition, multiplication, subtraction, and division. The User’s will input the two numbers into the application and the application will instantly calculate the resulting operation.

Key Features

• Perform addition, division, multiplication, and subtraction, among other basic arithmetic operations.
• Input through the command line or a GUI.

Libraries 

• Tkinter: Will provide the necessary interface to create the calculator window and buttons.
• math: Will provide the basic mathematical functions like square roots, trigonometry, etc.

Source Code: https://github.com/programiz/Calculator

8. Quiz Game

A simple interactive quiz game that presents multiple-choice questions to the user. Users will select answers to the questions, and the application will keep track of users' scores. It will be a fun way to learn and test knowledge on a variety of subjects.

Key Features

• Display multiple-choice questions and keep track of responses. 
• At the conclusion, show the score.

Libraries

• Tkinter: The GUI toolkit for creating the interface for the quiz questions.
• random: Will provide functions to randomise the quiz questions and answer options.

Source Code: https://github.com/shriyaa01/Python_Quiz_Game

These projects help enhance programming skills and can also serve as minor projects for final-year students, showcasing problem-solving abilities with manageable complexity. Here are the Intermediate-Level Python Projects:

1. Handwritten Character Recognition

This project will involve training a machine learning model to detect and classify handwritten characters (letters and digits) in image format. This will be done through deep learning in order to classify various different styles of handwriting.

Key Features

• Pre-process image data (resize, normalise).
• Train a neural network (for e.g., CNN) to classify characters.
• Predict handwritten characters from input images.
• Evaluate model performance as an accuracy score.
• Creates an interface that lets users upload or draw characters.

Libraries

• TensorFlow: It is a framework that allows you to create, build, and train neural networks.
• Keras: A high-level API to build and develop deep learning models using TensorFlow

Source Code: https://github.com/topics/handwriting-recognition

2. Hotel Booking Cancellation Rates Analysis

This project analyses hotel booking data to develop a predictive model to predict or explore motivation of hotel booking cancellations, typically used for improving management and decreasing cancellations.

Key Features

• Analyse the factors affecting hotel booking cancellations.
• Clean and process the data.
• Visualise the trends of cancellations with factors (e.g., by season, by region).
• Develop a prediction model of hotel bookings cancellations.
• Present the hotel with insights to mitigate the cancellations.

Libraries

• Pandas: Data manipulation and analysis tool.
• Matplotlib: Create and display data visualisations (charts, histograms, etc.)

Source Code: https://github.com/imuhammadaasim/hotel_bookings_cancelation

3. Smart Contact System

This project develops a decentralised application (DApp), which uses blockchain technology and can be defined based on way smart contracts allow for automation of tasks and transactions without the use of intermediaries.

Key Features

• Create and deploy digital agreements to the Ethereum network.
• Use smart contracts to automate transactions.
• Provide a web interface for people to engage with the blockchain.
• Security over contracts to guard against unauthorised access.
• Integrate with tools such as Metamask for transaction management.

Libraries

• web3.py: Python library to interact with the Ethereum blockchain and smart contracts.

Source Code: https://github.com/aanu2021/Smart-Contact-Manager

4. Movie Recommendation App

A recommendation system that makes movie suggestions to users according on their tastes and past viewing habits. This system employs machine learning algorithms, specifically a collaborative filtering algorithm, which personalizes each user's movie recommendations for an enriched movie watching experience.

Key Features

• Give movie recommendations to people based on their watching patterns and tastes.
• Develop and design a collaborative filtering recommendation system.
• Enable users to submit their ratings for each movie and take advantage of those ratings for personalized suggestions.

Libraries

• Scikit-learn: For recommendation systems, scikit-learn includes various machine learning algorithms (including collaborative filtering).
• Pandas: For processing and analyzing movie data to provide recommendations for personalized suggestions.

Source Code: https://github.com/rudrajikadra/Movie-Recommendation-System-Using-Python-and-Pandas/blob/master/Movie%20Recommender%20System.ipynb

5. Job Portal Scraper

This is a web scraping tool that extracts job listings from job sites and allows users to filter the results depending on their own choices (region, income, job title, etc.). This allows for the sequential collecting of suitable job possibilities.

Key Features

• Scrape job postings from job sites.
• Filter and classify jobs based on parameters including location, job title, and skills.
• View and save job ads.

Libraries

• BeautifulSoup: For scraping of job listing data from the HTML of job portals and parsing that data for the job listing.
• Requests: For fetching an HTML page and performing a web service call on a portal.

Source Code: https://github.com/ShoumikDutta/Job-Search-Web-Scraper

6. Student Performance Prediction

A Machine Learning model for predicting the academic performance of students based on historical data such as grades, attendance, and behavior data. The model can provide information regarding why students succeed, and provide education professionals with insights to make appropriate decisions.

Key Features

• Predict student grades or performance based on historical information.
• Analyze reasons for success, past grades, attendance, and student behavior.
• Construct a model to predict future academic success.

Libraries

• Scikit-learn: Machine Learning algorithms are implemented, providing predictions on student performance outcomes.
• Pandas: Library for data manipulation in order to prepare student performance data for analysis.

Source Code: https://github.com/shubhamtamhane/student-performance-python

₹ 49,000

₹ 33,000

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7. Library Management System

An automated system for keeping track of books, members, and transactions within a library. The system will keep track of the availability of books, allow staff to borrow and return books, keep track of whether books are available, manage members of the library, and provide a user interface for the staff to manage their inventory of books and members of the library.

Key Features

• Keep track of inventory, members, and transactions in a library.
• Keep track of the availability of books, the history of users borrowing each book, and the due dates for each user.
• Generate reports regarding the books borrowed and the due dates for each member.

Libraries

• Tkinter - Toolkit for designing the user interface to the tracking management system.
• SQLite - A lightweight database storing book information and transaction records.

Source Code: https://github.com/kunzbhatia/Library-Management-System

8. AI-Powered Personal Assistance

An intelligent virtual assistant that can schedule appointments, set reminders, answer questions, and control smart devices is among the best Python projects for final year students. A Virtual Assistant will make daily tasks more convenient and provide users with the capability to access their assistant via voice commands or typing.

Key Features

• Complete tasks such as scheduling, taking notes, or responding to queries.
• Voice-command action and feedback from the user.
• Communicate with other services via APIs, for instance, email or calendar.

Libraries

• SpeechRecognition: Provides access to a number of speech recognition engines that can take audio input and convert this audio into text.
• NLTK: Natural Language Toolkit, which is a real-time library for natural language processing, as well as identification and response to commands.

Source Code: https://github.com/ggeop/Python-ai-assistant

When considering a major project for your final year, the project must prove scalability, innovation, and sustainability. Major projects often address real-world problems and include substantial research before coding and testing.

These major projects typically set you apart from the other students by providing evidence of your capabilities for advanced coding and problem-solving. To clarify, here are the major projects on Python:

1. Real-Time Traffic Management System

A system that analyzes and manages traffic in real time using video feeds or sensors. The system detects traffic conditions, vehicle speeds, and congestion, and optimizes traffic flow by adjusting traffic light timings or alerting authorities.

Key Features

• Track live traffic by video or sensor setup.
• Detect vehicles and traffic congestion in live videos using OpenCV.
• Use scikit-learn to predict potential traffic conditions.
• Use appropriate libraries to advise traffic light cycle times.
• Alert relevant authorities of accidents and incidents or potential anomalies.

Libraries

• OpenCV: Library for Computer/Video recognition tasks (to detect vehicles or similar) as well as video processing and conversion.
• Scikit-learn: A Library for machine learning models to help predict traffic congestion patterns and to model the most effective traffic light cycle times.

Source Code: https://github.com/jayita13/AUTOMATED-TRAFFIC-MANAGEMENT-SYSTEM

2. Augmented Reality (AR) App

An application that augments the user's vision of the real world by combining a set of virtual objects or information into the real physical world. AR is frequently used for interactive experiences found in games, education, and visualization. Also, this can be one of the impressive Python projects for final year students as you will focus on the most advanced technologies and skills.

Key Features

• Composite 3D virtual objects into the real world.  
• Interact with AR objects (size, orientation).  
• Real-time tracking using a camera with depth and sensors.  
• Create interactive (AR) experiences with Pygame.  
• Support for object detection and gesture recognition. 

Libraries

• ARKit: A framework that allows people to make AR experiences (iOS-based, but you can use Python wrappers)  
• Pygame: A library to build interactive applications, it is often used to create AR games or educational tools. 

Source Code:  https://github.com/topics/augmented-reality-application?o=desc&s=updated

3. Cyberbullying Detection Using NLP

An approach to identify offensive and abbusive language in postings or discussions on social networking sites. Using methods from natural language processing (NLP) will assist in identifying instances of cyberbullying, with an alert to moderators or action taken before escalation can begin. 

Key Features

• Detect harmful or abusive language from a body of text.  
• Perform sentiment analysis (using TextBlob).  
• Text preprocessing (using NLTK).  
• Ask the system to classify messages as cyberbullying or not.  
• Generate alerts for flagged content. 

Libraries

• NLTK (Natural Language Toolkit): For text preprocessing and performing NLP tasks, such as tokenization and stemming.  
• TextBlob: For performing sentiment analysis and classification of text data..

Source Code:  https://github.com/kirtiksingh/Cyberbullying-Detection-using-Machine-Learning

4. AI Chatbot

An artificial intelligence chat system that can interact with users using Natural Language Processing (NLP) to process user inputs and generate human-like outputs. The chat system can simulate conversations, answer questions, and execute tasks through chat, making it a perfect fit for customer service and virtual assistants.

Key Features

• User text interaction
• Natural language processing for understanding
• Contextual conversation

Libraries

• NLTK: For text processing.
• TensorFlow/Keras: For training the model.

Source Code:  https://github.com/topics/chatbot

5. E-commerce Recommendation System

This system provides personalized product recommendations to users by analyzing their browsing and purchasing history. It utilizes machine learning models to generate recommendations tailored to the individual user, which improves the purchasing process experience and improves sales on e-commerce sites.

Key Features

• Personalized product recommendations
• Recommendations based on user data
• Improves user experience

Libraries

• Pandas: For manipulation of data
• Sci-kit learn: For recommendation models

Source Code: https://github.com/Vaibhav67979/Ecommerce-product-recommendation-system

6. Smart Attendance System

A facial recognition attendance system that can automate the process of taking attendance in schools/educational institutions or organizations. It takes pictures of users' faces, matches them with existing data, and takes attendance based on the matching pictures. It improves efficiency and accuracy in attendance.

Key Features

• Facial recognition attendance
• Real-time attendance processing
• Attendance data and study management

Libraries

• OpenCV: For image and face recognition.
• Dlib: For face feature detection.

Source Code: https://github.com/topics/attendance-system?l=python

7. Image Processing Project

This project is focused on using algorithms to process, improve, and analyze images. This may include image recognition, segmentation, and manipulation. Computer vision applications utilize many of these, from facial detection to object identification and medical imaging.

Key Features

• Image recognition.
• Image transformation and enhancement.
• Real-time processing.

Libraries

• OpenCV: mostly image processing tasks.
• Pillow: image manipulation.

Source Code: https://github.com/topics/image-processing-python

8. Automated Resume Screening System

The goal of this project is to develop a system that will automatically review resumes and assign a ranking based on a job description. In order to assist the HR department with its hiring process, the system will employ natural language processing to extract important data including experience, education, and talents.

Key Features

• Automatically filtering and ranking resumes based on job requirements.
• Extraction of important data, including job experience, credentials, and abilities.

Libraries

• NLTK: using the NLTK library, will process the resume text data for keyword matching and information feature extraction.
• Scikit-learn: classify and rank resumes using a machine learning model.

Source Code: https://github.com/raghavendranhp/Resume_screening

Here are some suggestions for how to implement your project using Python:

• Be sure to break the project into smaller components; once they are implemented individually, it is much easier to manage, develop, and test your project.
• Use Python's built-in debugger (pdb), or simply print statements for debugging, to assist you in identifying and correcting bugs as you develop.
• Use descriptive names for your variables, build docstrings in the header of your functions, and be consistent with your coding standards and style for readability.
• If desired, use a unit testing framework such as unit test or pytest to test each component and verify that it works as expected.
• Keep a fresh README, document key logic, and have a layout for presentation that includes visuals.

In summary, Python projects for final year students help improve coding skills, utilize favorable solutions to real-life problems, and serve as practical experience. Whether a minor project to amplify your most basic knowledge or a major project to exploit your highest abilities, Python has infinite options for innovative ideas. Selecting a project that reflects personal passion and career goals will help make your final year see your project as the stars must have aligned to support your skillset. Furthermore, each Python projects with source code will include access to the source code and ideas for modifications to initiate your project without defensiveness.

₹ 49,000

₹ 33,000

/-

Karthik was able to transform his career from a boring job to an exciting job in software!

Talk to a career expert

1. How do I select a suitable Python project idea for my final year?

Choose topics that relate to your known interests and career plans. Select a project that is exciting and pushes your abilities while also allowing enough time to complete.

2. How can I improve my debugging abilities in Python?

Practice using debugging tools such as pdb, add print statements, and write unit tests to catch early. Debugging abilities improve over time.

3. Why is documentation important in Python projects?

Documentation can improve the understanding of your code, provide meaning to others reading the code, and offer maintenance help. Documentation puts your thought process down on paper and allows other people to engage in your project more easily.

4. What key aspects do I need to include in my final project presentation?

Remember the theory in your project and what parts were completed. You should highlight aspects of the project such as problem definition, methodology, and results and conclusions. The use of visualizations helps people grasp the story you are telling. Show how your code works.

5. How to effectively test my Python project?

Divide the project into smaller, independent components and create unit tests for each method or module. Finally, use the testing framework, unit tests or pytest to test the code to ensure the code quality.