This repository contains comprehensive coursework, assignments, lab exercises, and project work completed as part of the Centre for Development of Advanced Computing (CDAC) curriculum. It is intended as both a reference for current students and a showcase of practical work across various domains of computer science and artificial intelligence.

• Certificates
• About
• Repository Structure
• Major Modules
• How to Use
• Contributing
• License
• Contact

-- CDAC PGDAI CERTIFICATE

-- CDAC PGDAI PERFORMANCE STATEMENT

The CDAC repository is a collection of learning artifacts, assignments, lab works, and project files spanning multiple key subjects in computer science and applied AI. It is organized to reflect module-wise progression and is ideal for revision, reference, or demonstration of skills gained during the CDAC program.

├── 1. Programming Fundamentals/
├── 2. Data Structures/
├── 3. AI TRENDS/
├── 4. Machine Learning/
├── 5. Natural Language Processing/
├── 6. Deep Learning/
├── 7. Java Programming/
├── 8. Computer Vision and Image Processing/
├── Web-based Teacher-Student Examination System/
└── README.md

Each directory contains module-specific assignments, lab exercises, and (where applicable) supplementary documentation.

• Programming Fundamentals: Core programming concepts, language basics, and introductory assignments.
• Data Structures: Implementation and practical usage of various data structures.
• AI Trends: Assignments and labs on contemporary topics in artificial intelligence.
• Machine Learning: Hands-on labs, projects, and theory in supervised/unsupervised learning.
• Natural Language Processing: Exercises and projects on language modeling, text analytics, and NLP tools.
• Deep Learning: Neural network assignments, coding labs, and experiments.
• Web-based Teacher-Student Examination System: Comprehensive system integrating NLP and Google Sheets for automated assessment.

1. Clone the repository:

   git clone https://github.com/ADVAIT135/CDAC.git
   cd CDAC

2. Browse module folders to access assignments, lab solutions, and projects.
3. Open relevant files in your preferred IDE or notebook environment for review or experimentation.

Contributions are welcome! If you find errors, want to add new resources, or improve existing ones, please fork the repository and submit a pull request.

Please refer to the repository for licensing details. If no license is present, all rights are reserved by the author.

• Author: ADVAIT135