17 Python Projects for Your Resume (Updated for 2024)

Python is a versatile and multi-purpose programming language ideal for data analysis and machine learning, thanks to its powerful libraries and community support.

By creating a portfolio of Python projects, you not only demonstrate your problem-solving abilities in real-world analytics problems, but you do so in the language most favored by employers and interviewers.

In this article, we have curated an extensive list of Python projects for resume and demonstrating your skills to future employers.

Including Python projects in your CV is useful for all job seekers, but especially for new graduates and candidates with limited professional experience.

A well-planned portfolio of projects will prove that you have the technical expertise and business acumen to excel in the role you are applying for. Further, it shows that you are willing to go the extra mile to communicate your skills, thus helping you differentiate yourself in a competitive job market.

Now that we understand the value of Python projects on your resume, let’s move on to the next section, where we’ll go into the most popular ones in more detail.

Here are 17 Python projects we recommend you consider including in your resume:

1. Web Scraper Tool

A web scraper is a Python-based application that automatically extracts data from websites. This project involves writing a script to send requests to web pages and parse the HTML content to retrieve information like product details, prices, news articles, or social media posts.

This is a valuable project for your CV, whether you are aiming for a job in tech, analytics, or any industry that values data-driven decision-making.

Scraping tools are used across industries for data collection, market research, lead generation, and competitive analysis. Web scraping requires a range of skills, including an understanding of HTML and CSS and working with APIs and libraries such as BeautifulSoup or Scrapy in Python.

Data.world has several web scraping open datasets that you can practice on. If you need help getting started, here is a tutorial on building a web scraper from scratch.

2. Chatbot With NLP

Chatbots are software applications designed to simulate conversations with human users. Using Python and NLP libraries like NLTK, spaCy, or TensorFlow, you can build your own chatbot to understand and process language and generate relevant responses.

A Python project to build a chatbot would involve training the program on large datasets to improve its conversation abilities. Chatbots can have basic features or be enhanced to include functionalities like sentiment analysis, answering questions, or performing specific tasks like bookings.

Chatbots are one of the most sought-after technologies in tech today, with applications in customer service, marketing, and even mental health support. Having this experience on your resume will show your future employers that you are skilled in NLP, AI, and advanced programming. It will also demonstrate that you are abreast of current tech trends.

To get started, you can use this resource to begin building your first chatbot. Microsoft has a great database to practice on, the WikiQA Corpus, which utilizes Bing query logs and Wikipedia pages as sources.

3. Automated Email Sender

This application can be built using Python to automate the task of sending emails, especially for campaigns or repetitive email tasks. You could use the PyAutoMail library, with libraries like MIME for more advanced features.

Showcasing this project is valuable as it demonstrates skills in automation, working with email protocols, and integrating with other services or databases, which are highly valued skills in most industries for communication and marketing.

For a helpful tutorial, you can refer to the PyAutoMail repository on GitHub.

4. GUI (Graphical User Interface)

A Graphical User Interface (GUI) is the graphic that the user of a product interacts with when they open an application. This project involves creating an application with a visual interface, including buttons, text fields, labels, and various other interactive elements. Python offers several libraries for GUI development, such as Tkinter, PyQt, or Kivy, each with its unique features.

As a developer, your ability to build applications with user intent in mind while showcasing skills in design, event-driven programming, and cross-platform development is hugely important. Such projects indicate an understanding of user experience and the ability to translate product offerings in an accessible way to non-technical users.

You can practice from a range of projects in this repository.

5. Website

Building a website involves creating a web application with a backend (server-side logic) and a frontend (user interface). Python frameworks like Flask and Django are popular choices for this purpose.

Flask is more lightweight and flexible, ideal for smaller projects or microservices, whereas Django offers more built-in features, making it suitable for larger, more complex applications. You can choose the framework depending on whether you want to build a standard website or an interactive one like a time zone converter.

You’ll also need to use HTML, CSS, and JavaScript to design the user interface. Finally, you can deploy it to a server through platforms like AWS or Heroku.

Web developer roles are sought-after and lucrative, so having this project is a must-have if you are vying for such a role. This is a crucial skill as a developer in numerous industries as well. Get started with a Flask tutorial here.

Start with a simple project like a basic e-commerce site or portfolio website. When you are ready to handle more complex tasks, you can try something challenging, like a website that converts time zones.

6. Weather Application

This is a program that retrieves and displays weather information from an external weather API. The tool helps users view weather data, forecasts, and other climate-related information.

You will need to fetch data from a weather API such as AccuWeather or OpenWeatherMap. You can use Python’s requests library for this purpose. Process the API response (usually in JSON format) and display the data. For the GUI, libraries like Tkinter or PyQt can be used, as mentioned above.

For landing roles in software development, the ability to build a weather application illustrates your skill in working with external APIs, handling real-time data, and GUI development. These are invaluable skills that you will require constantly in your job.

Here are three repositories you may refer to on this topic. Also, sign up for a free API key from a weather data provider to practice fetching and displaying weather data.

7. Game Development

If you have a passion for gaming, why not try your hand at creating games using Python? This skill is highly coveted in the gaming industry, and you can have some fun in the process, too!

You can showcase this as a transferable skill in other roles in the entertainment or education sectors where interactive content creation is valued. Having done this project will demonstrate your creativity in solving complex logical challenges and proficiency in advanced programming.

The most popular library for this purpose is Pygame, which provides functionalities for creating game elements, handling events, managing graphics, and playing sounds. You’ll need to develop the logic first and then handle the design, such as graphics and sound. Refer to this Pygame tutorial to get started.

Idea: Build a classic game like Tetris or Snake.

8. Inventory Management System

Building an application designed to manage and track inventory levels, orders, sales, and deliveries has huge potential in sectors like retail, logistics, and supply chain management. The design usually involves a database to store inventory data and a user interface for data entry and reporting.

This process will involve three major steps: designing the database, building the backend logic to track and query the inventory, and creating a user interface.

Adding this project to your professional portfolio will tell your potential interviewer that you are competent in end-to-end software solutions, with skills in Python as well as database management.

You can refer to these repositories to get started.

9. Personal Finance Tracker

You can have a go at developing an application to manage personal financial information, including expenses, income, budgets, and savings. This can include features to record transactions, categorize expenses, and visualize financial data.

To deploy this tool, create dummy data, store it in a database using SQL (for example), and analyze and report it through visualizations using matplotlib and pandas. Create a GUI using libraries like Tkinter or PyQt, or develop a web-based interface using Flask or Django for user interaction.

This project will reflect your understanding of data handling and visualization, as well as your ability to deploy tools with user design in focus. These skills will be useful across a range of Python-based developer roles and jobs in finance, banking, and analytics. There are plenty of repositories you can refer to on GitHub if you feel stuck.

10. Sales Forecasting

This analytics project is to build a robust model to predict nationwide retail store sales for each store and department, for a particular company.

An important piece of information is given to you: their sales are seasonal, and they make a significant proportion of their revenue during holidays like the Super Bowl, Labor Day, Thanksgiving, and Christmas.

To work on this prediction project, remember to incorporate date-related features into your model, such as holiday flags and even the days leading up to these events.

For predictive modeling, libraries like scikit-learn are suitable for regression tasks; you can start with simple linear regression and then move on to complex models to check if the accuracy improves. Finally, evaluate the model’s performance using appropriate metrics.

Having this project in your CV shows that you have tackled a real-world retail problem and understand how to analyze seasonality. Highlight the logic behind your feature engineering to showcase your critical thinking skills.

11. Twitter Sentiment Analysis

The purpose of this project is to prototype a system to monitor the relationship between cryptocurrency prices and the sentiment of tweets surrounding the coins of interest.

Thoroughly preprocess the raw data files by cleaning, tokenizing, and removing stop words. Employ Python libraries like NLTK or spaCy to analyze Twitter sentiment. The correlation can be computed using Pearson’s correlation coefficient. Finally, visualize your results using matplotlib. Optionally, you can incorporate a predictive model to predict price changes based on sentiment data.

Including this project highlights your skills in NLP (Natural Language Processing), statistics, and critical thinking; skills that are extremely valuable in the context of the data science job market or even in tech and finance roles.

12. Human vs Bot Language Classifier

In this project, you are given two files containing text strings developed by humans and bots. Using these two sets of data, you need to deploy a model to classify the two sets, i.e., given a new data point, it will determine the appropriate label.

Here, you’ll need to extract features from the two texts using techniques like TF-IDF (Term Frequency-Inverse Document Frequency) for word importance, n-grams for capturing word sequences, or even NLP techniques like word embeddings (Word2Vec, GloVe). Choose a suitable model for classification, starting with simpler algorithms.

This Python project will demonstrate your advanced machine learning and NLP knowledge and that you can translate that knowledge into a real-world application. With the increasing prevalence of bots, the successful deployment of this project will place you at the forefront of Data Scientist and Machine Learning Engineer roles.

13. Rental Price Analysis

Understanding data on short-term rental prices and occupancy is very important to rental companies as it helps them with pricing decisions and benchmark occupancy and revenue against similar properties. This business case is a great project to add to your Python portfolio, as it is a challenging problem being tackled across companies and sectors.

In this take-home assignment, the way you handle features is crucial to deploying a successful model. Doing a correlation analysis or feature importance from tree-based models can be useful. Build a robust model and fine-tune it using cross-validation. Validate it on the test set using metrics like RMSE (Root Mean Square Error) or MAE (Mean Absolute Error).

14. EDA On Unusual Data

The media consulting firm VaynerMedia uses data to generate marketing insights for its clients. This take-home assignment, which is given to marketing analysts at the company, asks you to do some data preparation in Pandas and then generate a report with basic insights.

It asks you to merge two datasets and report key findings. If you’re looking at marketing analyst roles, an exploratory data analysis assignment is good to have on your resume. Since an EDA isn’t a business case problem in itself, make sure to explain the purpose of this project, what your learnings were, and how you can apply them to real-world scenarios.

15. Credit Card Fraud Detection

A very valuable data science project is fraud detection. In this assignment, you are given dummy credit card transaction data. Fraud can take many forms, ranging from card theft, large batches of stolen card numbers being used on the web, to a mass compromise of card numbers stolen from a merchant via credit card skimming devices.

You will need to come up with a set of rules to determine whether an action is fraudulent and then build a classification model to implement these rules so that you can classify a new data point as fraudulent or not.

The main thing to remember is that your logical reasoning is the main contributor to this project’s success. Make sure to understand the problem statement and develop a comprehensive set of rules before you start working on the model deployment.

16. Electricity Pricing Model

The energy consulting firm CleanSpark uses data to analyze electricity bills for commercial facilities. This take-home assignment is given to data analysts at the company and involves calculating energy and demand charges using electricity consumption data. Your task is to implement two functions in Python to calculate these charges based on the given data and pricing scheme. This assignment will demonstrate your data processing and analytical skills in a practical business scenario.

This project highlights the importance of accurate billing and energy management for commercial facilities. By understanding and applying these concepts, it can help businesses optimize their energy consumption and reduce costs. Additionally, this analytical approach can be applied to various domains where data-driven decision-making is crucial.

17. Delivery Time Estimator

The food delivery company DoorDash uses data to improve customer experience by accurately predicting delivery times. This take-home assignment, designed for data scientists, tasks you with building a machine learning model to predict total delivery duration and developing a corresponding application. The exercise is divided into two parts: model building and application development. Your performance will be evaluated on your modeling choices, feature engineering, data processing, and the performance of your application in making predictions.

In the first part, you will use historical delivery data to build a model predicting delivery duration. This involves feature engineering, data processing, and model selection, with your evaluation based on the test set performance and the insights you derive. The second part requires you to write an application in Python that uses your model to predict delivery times from a JSON file and outputs the results in a TSV format. This application must adhere to common software engineering patterns, demonstrating your ability to write clean, modular, and well-tested code.

1. Project Title and Description

Have a clear title and description to outline the project’s purpose, the Python libraries or frameworks used, and the problem it solved. Use action verbs like “developed,” “built,” “implemented,” or “analyzed” to persuade your potential interviewers. Have a brief section on the results/key insights of the project.

2. Highlight Technical Skills

Emphasize specific Python skills and libraries in your resume. If you have elementary proficiency in a framework, for example, you should include this keyword and mention that you are a beginner, simply to bolster your chances of getting an interview.

3. Quantify Achievements

Wherever possible, quantify the impact of your project. If you worked on it in a previous firm, you can highlight the hours saved or the revenue impacted. If this project was a personal initiative, you can still mention features such as the model’s accuracy or the fine-tuning that led to improved model performance.

4. Mention Collaborative Work

If the project was part of a team or a collaborative effort, mention your role and contribution to show that you are a team player. Teamwork and collaboration skills are highly valued by employers.

5. Link to GitHub Repository

If you have the projects hosted on GitHub, include a link to the repository. This provides employers with direct access to your code and demonstrates transparency in your work.

6. Tailor to Job Description

Align your project descriptions with the job and sector requirements. For instance, if you’re applying for a data science role, emphasize projects related to data analysis, machine learning, or statistical modeling. Remember that the projects section of your resume is a chance to demonstrate hands-on experience, so make sure it’s clear, concise, and relevant to the role and industry you’re applying for.

To wrap up, incorporating Python projects into your resume is a clever strategy to showcase your hands-on experience and set you apart in a competitive job market. Try to plan your interview strategy, taking the perspective of your desired future employer into account, and tailor your project selection according to the skills they would want to see.

Try checking out our recommended Data Science Projects in Python if you’re looking for a good data science resume. At the same time, you can also check out our premium Python learning path, which is tailored to help aspirants like yourself. However, that decision is completely up to you.

We know you will land that dream job with hard work, good planning, and confidence, and wish you all the very best on your journey!