Master - Big Data & Business Intelligence

Welcome to the official GitHub repository of the Master - Big Data & Business Intelligence at ENSA Khouribga!

Overview

Explore a curated collection of courses, practical works, and projects developed by our Master's students in Big Data and Business Intelligence. This repository is a testament to their dedication, creativity, and expertise in the realms of data analytics, business intelligence, and big data technologies.

Works

The repository contains all the resources, practical works, and projects created by the students. Feel free to explore each subject and discover its contents:

1. Business Intelligence:

   • Presentations: View presentations created by the students.
   • Practical Exercises: Practice materials for BI concepts.
   • Projects: Explore projects in the field of BI.

2. Cryptography:

   • Courses: Access course materials related to cryptography.
   • Exams: Materials for exam preparation.
   • Presentations: Presentation files.
   • Projects: Projects related to cryptography algorithms.

3. Data Analysis:

   • Courses: Courses on data analysis techniques.
   • Exams: Exam resources.
   • Guided Exercises: Guided exercises for practical learning.
   • Practical Work: Practical assignments for data analysis.
   • Projects: Data analysis projects.

4. Data Mining and Text Mining:

   • Courses: Courses on data and text mining.
   • Practical Work: Hands-on exercises for mining techniques.
   • Presentations: Presentation materials.

5. Graphs Theory:

   • Algorithms: Implementation of graph algorithms.
   • Courses: Graph theory courses.
   • Exercises: Exercises for practicing graph theory.
   • Guided Work: Guided projects on graph theory concepts.
   • Resumes: Summaries of graph theory topics.

6. Image Processing:

   • Courses: Courses on image processing.
   • Examples: Example projects and code snippets.
   • Practical Work: Hands-on exercises in image processing.
   • Projects: Projects involving image processing techniques.

7. Mathematics For Big Data:

   • Code Implementations: Implementations of mathematical concepts.
   • Courses: Courses on mathematical topics for big data.
   • Practical Exercises: Hands-on exercises for mathematical concepts.
   • Presentations: Presentation materials.
   • Reports: Reports on mathematical topics.

8. Python and Java OOP:

   • Courses: Courses on object-oriented programming in Python and Java.
   • Practical Exercises: Hands-on exercises for OOP concepts.
   • Projects: Projects involving OOP in Python and Java.
     • Machine Learning Algorithms Collection App: A collection app for machine learning algorithms.

9. Recherche Operationnel:

   • Courses: Courses on operational research.
   • Exams: Exam materials.
   • Exercises: Practice exercises.
   • Guided Work: Guided projects.
   • Practical Work: Hands-on practical assignments.

10. Research Methodology:

    • Courses: Courses on research methodology.
    • Projects: Research projects.
      • Articles: Research articles.

Contributing

We welcome contributions from students, educators, and professionals. Whether you want to add new projects, enhance existing materials, or fix bugs, your contributions are highly appreciated. Please refer to our contribution guidelines for more details.

License

This project is licensed under the MIT license.