This repository contains the complete source code, Jupyter Notebooks, datasets, and analysis reports developed during my Data Science Internship at CodeAlpha.
As per the internship requirements, I successfully completed 4 out of the 4 assigned tasks, covering both Classification and Regression machine learning models, along with exploratory data analysis (EDA) for economic trends.
Internship Duration: 2026/08/01 – 2026/08/31
| Task No. | Project Name | Domain | Status |
|---|---|---|---|
| Task 1 | Iris Flower Classification | Classification (Supervised) | ✅ Completed |
| Task 2 | Unemployment Analysis with Python | EDA & Time-series | ✅ Completed |
| Task 3 | Car Price Prediction | Regression | ✅ Completed |
| Task 4 | Sales Prediction | Regression / Forecasting | ✅ Completed |
Note: I completed 4 tasks.
- Languages: Python 3.x
- Data Processing: Pandas, NumPy
- Visualization: Matplotlib, Seaborn
- Machine Learning: Scikit-learn (Linear/Logistic Regression, Decision Trees, Random Forest)
- Environment: Jupyter Notebook
Since all tasks are independent, you can navigate into each task's folder and run the .ipynb or .py file individually.
- Clone the repository:
git clone https://github.com/lipril/codealpha_tasks.git cd codealpha_tasks - Install the required global dependencies:
pip install -r requirements.txt
OMAR IBN WAZED
Made with ❤️ during my Data Science Internship at CodeAlpha. Completed by OMAR IBN WAZED