3 Beginner-Friendly Data Science Projects to Build Your Portfolio in 2025

👩‍💻 Want to Break into Data Science but Don’t Know Where to Start?

The best way to begin your data science journey is with hands-on projects using real-world datasets. These beginner-friendly Kaggle competitions will help you gain practical skills in data cleaning, model building, and evaluation — all while making your resume stand out.

Whether you’re just starting out or transitioning from another field, these projects are perfect to build your confidence and portfolio.

𝐏𝐚𝐲 𝐀𝐟𝐭𝐞𝐫 𝐏𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐏𝐫𝐨𝐠𝐫𝐚𝐦- 𝐆𝐞𝐭 𝐏𝐥𝐚𝐜𝐞𝐝 𝐈𝐧 𝐓𝐨𝐩 𝐌𝐍𝐂'𝐬

📁 Top 3 Data Science Projects for Beginners on Kaggle

1. 🏠 House Prices: Advanced Regression Techniques

Skills Covered: Data preprocessing, feature engineering, regression models (Linear, Ridge, Lasso)
Project Goal: Predict house sale prices using various features.
✅ Perfect for learning how to clean messy data and work with continuous target variables.

2. 🚢 Titanic: Machine Learning from Disaster

Skills Covered: Classification models (Logistic Regression, Decision Trees), handling missing data, feature selection
Project Goal: Predict which passengers survived the Titanic shipwreck.
✅ Ideal for complete beginners to practice binary classification.

3. 🔢 Digit Recognizer (Computer Vision)

Skills Covered: Image data, pixel-based feature extraction, neural networks
Project Goal: Identify handwritten digits using the MNIST dataset.
✅ Great introduction to computer vision and working with image-based datasets.

🎯 Why You Should Do These Projects

Hands-on experience with real datasets
Learn industry-standard techniques
Build a portfolio to showcase in interviews
Practice using Python, Pandas, Scikit-learn, and more
Improve problem-solving and model evaluation skills

📌 Final Tip:

Make sure to document your work clearly, upload your notebooks to GitHub, and add project links to your resume or LinkedIn profile.

Start today, grow your skills, and move one step closer to a career in data science!

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