🚀 QSkill Python Internship Projects

📌 Overview

This repository contains three practical Python projects developed during my 1-Month Python Internship at QSkill.

Each project focuses on a different area of Artificial Intelligence, Machine Learning, and Backend Development.

The repository demonstrates hands-on implementation of:

• AI Agent Development
• Machine Learning Model Training
• REST API Development
• Natural Language Processing
• Environment Variable Management
• Model Serialization

---

📂 Repository Structure

QSKILL
│
├── agent_engine
│   └── enterprise_agent.py
│
├── regression_engine
│   ├── train.py
│   ├── predict.py
│   ├── housing_data.csv
│   └── valuation_model.pkl
│
├── sentiment_api
│   └── app.py
│
└── .gitignore

---

🤖 Project 1 — AI Enterprise Agent

An intelligent conversational assistant powered by Google Gemini with integrated real-time web search.

Features

• Google Gemini 2.5 Flash
• Stateful chat session
• DuckDuckGo real-time search
• Automatic function calling
• Environment variable security
• Session memory
• Professional prompt engineering

Technologies

• Google Gemini SDK
• DuckDuckGo Search
• Python
• python-dotenv

---

📈 Project 2 — House Price Prediction

A machine learning regression project that predicts property prices based on property characteristics.

Features

• Synthetic dataset generation
• Linear Regression model
• Model serialization using Pickle
• Train/Test split
• RMSE evaluation
• R² Score evaluation
• Real-time prediction script

Input Features

Feature	Description
Rooms	Number of rooms
Size	Area in square feet
Location Grade	Property location rating

Output

Estimated Property Price (Lakhs INR)

---

💬 Project 3 — Sentiment Analysis REST API

A Flask-based REST API that analyzes text sentiment using TextBlob.

Features

• RESTful API
• JSON request validation
• Text polarity analysis
• Subjectivity analysis
• Positive / Neutral / Negative classification
• Standardized JSON responses
• Error handling

Example Endpoint

POST /api/v1/sentiment

Example Request

{
    "text":"This internship was amazing!"
}

Example Response

{
  "status":"success",
  "data":{
      "classification":"Positive",
      "metrics":{
          "polarity_score":0.75,
          "subjectivity_score":0.6
      }
  }
}

---

🛠 Tech Stack

• Python
• Google Gemini API
• Flask
• TextBlob
• Scikit-learn
• Pandas
• NumPy
• DuckDuckGo Search
• Pickle
• dotenv

---

⚙ Installation

Clone the repository

git clone https://github.com/imarpitajaiswal/QSKILL.git

cd QSKILL

Install dependencies

pip install -r requirements.txt

Create a .env file

GEMINI_API_KEY=YOUR_API_KEY

---

▶ Running the Projects

AI Agent

python agent_engine/enterprise_agent.py

Train Regression Model

python regression_engine/train.py

Predict Property Price

python regression_engine/predict.py

Start Sentiment API

python sentiment_api/app.py

---

📚 Learning Outcomes

During this internship, I gained practical experience in:

• Python Programming
• AI Agent Development
• REST API Design
• Machine Learning
• Data Preprocessing
• Model Evaluation
• Environment Variable Security
• Natural Language Processing
• Version Control using Git & GitHub

---

🚀 Future Improvements

• Docker Support
• FastAPI Migration
• Model Deployment
• Streamlit Dashboard
• Authentication
• Database Integration
• CI/CD Pipeline
• Unit Testing

---

👩‍💻 Author

Arpita Jaiswal

MCA (Artificial Intelligence & Machine Learning)

GitHub: https://github.com/imarpitajaiswal

LinkedIn: https://linkedin.com/in/imarpitajaiswal

---

⭐ If you found this repository useful, consider giving it a star.