Welcome to my CodeAlpha Data Analytics Internship repository.
This repository contains the projects completed during my Data Analytics Internship at CodeAlpha. The internship focuses on developing practical skills in data analysis, visualization, and machine learning by solving real-world problems using industry-standard tools and techniques.
- Organization: CodeAlpha
- Domain: Data Analytics
- Intern: Zain Latif
- Student ID: CA/DF1/174112
- Duration: 1 July 2026 – 30 July 2026
The purpose of this repository is to document my internship journey by completing the assigned projects and showcasing my analytical, visualization, and problem-solving skills.
Each task includes source code, datasets (where permitted), reports, visualizations, and documentation.
Extract data from websites using Python libraries such as BeautifulSoup or Scrapy to create custom datasets for analysis.
Analyze datasets to identify trends, patterns, correlations, and insights through statistical methods and visual exploration.
Create meaningful charts, graphs, and dashboards using Python visualization libraries to communicate data-driven insights effectively.
Perform Natural Language Processing (NLP) on textual datasets to classify sentiments and analyze public opinions.
Note: As per the internship requirements, only the required tasks will be completed and submitted.
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Scikit-learn
- BeautifulSoup
- Jupyter Notebook
- Power BI
- Git & GitHub
codealpha-data-analytics-internship/
│
├── Task-1-Web-Scraping/
├── Task-2-EDA/
├── Task-3-Data-Visualization/
├── Task-4-Sentiment-Analysis/
└── README.md
- Data Collection
- Data Cleaning & Preprocessing
- Exploratory Data Analysis
- Statistical Analysis
- Data Visualization
- Natural Language Processing
- Insight Generation
- Reporting & Documentation
Zain Latif
- GitHub: https://github.com/zainlatif
- LinkedIn: https://linkedin.com/in/zainlatif702
- Kaggle: https://www.kaggle.com/zainlatif
Special thanks to CodeAlpha for providing this internship opportunity and hands-on projects that strengthen practical skills in Data Analytics.
If you find this repository helpful, feel free to star ⭐ it.