Welcome to the Intelligent Automation Projects Repository. This repository contains 10 hands-on labs that demonstrate the application of Intelligent Automation (IA) across various domains and use cases. Each lab is self-contained and showcases how AI, BPM, and RPA technologies integrate to streamline processes and drive business transformation.
Intelligent Automation (IA) is the combination of multiple automation technologies — primarily Artificial Intelligence (AI), Business Process Management (BPM), and Robotic Process Automation (RPA) — to automate complex business processes and decision-making.
| Pillar | Description | Examples |
|---|---|---|
| RPA | Software bots handle repetitive, rule-based tasks | File management, web scraping, email handling |
| AI | Machine learning and NLP analyze data and generate insights | Sentiment analysis, image classification, chatbots |
| BPM | Workflows orchestrate and route tasks across systems | API-driven pipelines, approval processes, notifications |
| # | Lab | Pillar | Key Technology | Difficulty |
|---|---|---|---|---|
| 01 | File & Folder Automation | RPA | watchdog, pathlib, shutil |
Beginner |
| 02 | Web Scraping & Data Extraction | RPA | BeautifulSoup4, requests, pandas |
Beginner |
| 03 | Email Automation | RPA | smtplib, imaplib, schedule |
Beginner |
| 04 | PDF & OCR Document Processing | RPA + AI | pdfplumber, pytesseract, Pillow |
Intermediate |
| 05 | NLP Sentiment Analysis Pipeline | AI | nltk, scikit-learn, matplotlib |
Intermediate |
| 06 | ML Predictive Analytics Pipeline | AI | scikit-learn, pandas, joblib |
Intermediate |
| 07 | API-Driven Process Automation | BPM | FastAPI, httpx, schedule |
Intermediate |
| 08 | Computer Vision & Image Processing | AI | OpenCV, Pillow, scikit-learn |
Intermediate |
| 09 | Conversational Chatbot | AI | nltk, Flask, transformers |
Intermediate |
| 10 | End-to-End IA Pipeline | AI + BPM + RPA | Integrates Labs 2, 4, 5, 6, 7 | Advanced |
┌─────────────────────────────────────────────────────────┐
│ RPA Layer │
│ Lab 01: File Automation Lab 02: Web Scraping │
│ Lab 03: Email Automation Lab 04: OCR / PDF │
└────────────────────────┬────────────────────────────────┘
│
┌────────────────────────▼────────────────────────────────┐
│ AI Layer │
│ Lab 05: Sentiment Analysis Lab 06: ML Pipeline │
│ Lab 08: Computer Vision Lab 09: Chatbot │
└────────────────────────┬────────────────────────────────┘
│
┌────────────────────────▼────────────────────────────────┐
│ BPM Layer │
│ Lab 07: API Workflow Automation │
└────────────────────────┬────────────────────────────────┘
│
┌────────────────────────▼────────────────────────────────┐
│ Integration Layer (Lab 10) │
│ Scrape → Extract → Analyze → Predict → Notify │
└─────────────────────────────────────────────────────────┘
- Python 3.9+
pippackage manager- Tesseract OCR (for Lab 04):
sudo apt install tesseract-ocr - OpenCV system dependencies (for Lab 08):
sudo apt install libgl1
# 1. Navigate to a lab directory
cd Lab-01-File-And-Folder-Automation
# 2. Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# 3. Install dependencies
pip install -r requirements.txt
# 4. Follow the lab READMEEach lab's README.md contains detailed setup instructions, explanations of key concepts, and step-by-step usage guides.
Intelligent-Automation/
├── README.md
├── .gitignore
├── Lab-01-File-And-Folder-Automation/
│ ├── README.md
│ ├── requirements.txt
│ ├── src/
│ └── data/
├── Lab-02-Web-Scraping/
│ ├── README.md
│ ├── requirements.txt
│ ├── src/
│ └── data/
...
└── Lab-10-End-To-End-IA-Pipeline/
├── README.md
├── requirements.txt
├── src/
└── data/
This repository is licensed under the GNU General Public License v3.0.