10 Best Data Science Projects to Get Hired and You Must Know in 2024

You have given your time and gained data science skills, but not getting a data science job. If you are in the same state, then it’s time to do some data science projects. That’s why I am gonna share some Best Data Science Projects to Get Hired. These projects will definitely boost your resume and make you different from the data science crowd.

So after reading this article, start doing some good data science projects. Now without further ado, let’s get finding the best data science projects to get hired-

Best Data Science Projects to Get Hired

1. Color Detection with Python

This is a beginner level project, where you have to build an interactive app. This app will identify the selected color from any image. There are 16 million colors based on the different RGB color values, but we only know a few colors.

So to implement this project, you need to have a labeled dataset of all the colors that we know, and then you need to calculate which color resembles the most with the selected color value.

In order to implement this project, you should be familiar with Computer Vision Python libraries- OpenCV and Pandas.

You can check all the details regarding this project here.

2. Facebook AI’s DEtection TRansformer (DETR)

This is an Open Source project by DETR by Facebook AI. This is the most interesting project by Facebook AI. DETR (DEtection TRansformer) is an innovative and efficient approach to solve the object detection problem. DETR is extremely fast and structured.

In Computer Vision, object detection is a problem where we want our model to differentiate the foreground objects from the background. And predict the places and the categories for the objects present in the image.

You can check the original paper published on DETR here and the source code for this project on GitHub.

3. Fake News Detection

There are lots of fake news spreading all over the world. So how can we differentiate between true news and false news?… The answer is with the help of Python. In this project, you have to build a model by using the Python programming language, which can identify whether the news is true or fake.

In order to implement this project, you need to build a TfidfVectorizer and use a PassiveAggressiveClassifier to classify news into “Real” and “Fake”. 

You can check the tutorial of this project in Datacamp and in DataFlair.

4. Name Game: Gender Prediction using Sound

This project is offered by Datacamp, where you have to identify the gender of the author of the New York Times Best Seller list for Children’s Picturebooks.

By using Python package Fuzzy, you have to search the author name in the dataset given by the US Social Security Administration, then aggregate the author dataset by including gender. And in the end, you have to use a new dataset to plot the gender distribution of authors.

In order to implement this project, you should be familiar with pandas, NumPy, and Matplotlib. You can check the project details here.

5. Real-Time Image Animation

This is an open-source project on computer vision. In this project, you have to perform image animation in real-time using OpenCV. Something like that. I have taken this image from the project’s GitHub repository.

As you can see in the image, the model mimics the expression of the person in front of the camera and changes the image expression accordingly.

This project is useful, especially if you are planning to enter into the fashion, retail, or advertising industry. You can check the code of this project at GitHub and Colab notebook too.

6. Phyllotaxis: Draw Flowers Using Mathematics

This project is perfect if you want to test and showcase your data visualization skill to the recruiter. In this project, you will use R to create imaginary flowers inspired by nature.

In order to complete this project, you should be familiar with the ggplot2 package. You can check the project details at Datacamp.

7. Speech Emotion Recognition

In this project, you have to build a model that can recognize human emotion and affective states from speech. Speech Emotion Recognition (SER) is one of the most challenging tasks in the speech signal analysis domain.

Speech Emotion Recognition can be used in various fields like customer service, recommender system, medical field, etc.

In this project, you will use librosa to perform Speech Emotion Recognition. You will build MLPClassifier for the model. You can check the project tutorial at PythonCode.

8. Movie Recommendation System using Collaborative Filtering

In this project, you have to create a recommendation system using Collaborative Filtering with help of the Scikit-surprise library. This system learns from the past behavior of customers.

This project will be good for you if you are starting your data science journey and want to showcase your real-world hands-on experience with recommendation systems.

You can check the project details at Coursera.

9. A New Era of Data Analysis in Baseball

In this project, you will use Statcast data to compare the home runs of two of baseball’s players- Aaron Judge (6’7″) and Giancarlo Stanton (6’6″). In this project, you will use Python programming language and perform data cleaning, data manipulation, and data visualization.

You can check the project details at Datacamp.

10. Credit Card Fraud Detection Project

In this project, you have to perform the detection of credit cards by using R programming and algorithms like Decision Trees, Logistic Regression, Artificial Neural Networks, and Gradient Boosting classifiers.

You will use the Card Transactions dataset to classify credit card transactions into fraudulent and genuine. And you will apply different machine learning algorithms and check the accuracy by plotting the performance curves.

You can check the Project Tutorial at DataFlair.

Conclusion

So these are some best data science projects to get hired. I hope you have found the most suitable project in this article for you. For more project ideas, you can check Kaggle, Datacamp, Coursera, DataFlair, etc.

If you have any questions, feel free to ask me in the comment section. I am here to help you. And If you found this article helpful, share it with others to help them too.

All the Best for your Data Science Journey!

Happy Learning!

Thank YOU!

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Though of the Day…

‘ It’s what you learn after you know it all that counts.’

– John Wooden