A List of Data Science Projects for Your Resume: Python

If you needed a list of Data Science Projects for your resume, you have to seek no other. We have listed them here for you.

Why Python for Data Science

Python plays a crucial role in data science projects due to its versatility and robust ecosystem of libraries like NumPy, Pandas, and Scikit-learn. Analysts utilize Python’s concise syntax and extensive libraries for data manipulation, analysis, and visualization. Its active community continuously develops tools and frameworks, enhancing the efficiency of tasks such as machine learning and statistical modeling. Python’s seamless integration with other technologies simplifies data preprocessing, exploration, and modeling, facilitating faster insights and decision-making processes. Its popularity among data scientists ensures a wealth of resources and support, making Python indispensable for tackling complex data challenges in various industries.

Why You Must Begin Creating Projects for Your Resume

Adding data science projects to your resume enhances its appeal by showcasing your practical skills and problem-solving abilities. Employers value tangible examples of your proficiency, and projects provide just that. By actively engaging in data science projects, you demonstrate your initiative and dedication to the field. Furthermore, these projects serve as evidence of your capability to apply theoretical knowledge to real-world scenarios, making you a more attractive candidate. Ultimately, incorporating data science projects into your resume not only bolsters your credibility but also increases your chances of securing opportunities in the competitive field of data science.

We have added the following list of projects for your refrence.

Easy Level

1. Sentiment Analysis
2. Fake News detection
3. Detecting Parkinsons’s Disease
4. Color Detection
5. Iris Data Set – Predict the class of the flower
6. Loan Prediction – Predict if a loan will get approved or not.
7. BigMart Sales Dataset – Predict the sales of a store.
8. House Price Regression
9. Wine quality – Predict the quality of the wine.
10. Heights and Weights Dataset – Predict the height or weight of a person
11. Email Classification
12. Titanic dataset

Intermediate Level

1. Speech Emotion Recognition
2. Gender and Age Detection
3. Driver Drowsiness detection
4. Basic Chatbot
5. Handwritten Digit Recognition
6. Black Friday Dataset – Predict purchase amount.
7. Trip History Dataset – Predict the class of user.
8. Song recommendation
9. Handwritten Text Recognition
10. Sentiment analysis – IMDB movie review dataset
11. Text generation – Shakespeare
12. Sign language MNIST classification

Advanced Level

1. Image Captioning
2. Recommendation System
3. Customer Segmentation
4. Breast Cancer Classification
5. Traffic Signs Recognition
6. Urban Sound Classification
7. Human Activity Recognition
8. Covid-19
9. Video classification
10. Fire and smoke detection
11. Detecting Natural Disasters
12. Anonymizing faces
13. Text Summarization
14. Deep Dream and Style Transfer

To view the code for the above projects, we recommend you to visit: https://github.com/veb-101/Data-Science-Projects