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📚 BS Data Science Complete Course Repository (FAST NUCES)

Welcome to the BS Data Science Complete Course Repository! This repository is designed specifically for the students of FAST NUCES, containing comprehensive resources from my eight semesters of coursework, notes, books, course outlines, assignments, lab works, and readings. It aims to aid juniors and anyone interested in pursuing a degree in Data Science at FAST NUCES.

Repository Structure 📂

The repository is organized into directories by semester, each containing subdirectories for individual courses. Here’s a detailed breakdown of the contents and how to navigate and use them:

  • Course Outlines: Detailed syllabi for each course.
  • Notes: Lecture notes and important concepts covered in class.
  • Books: Recommended textbooks and reading materials.
  • Assignments: Homework and project assignments with solutions.
  • Lab Works: Practical lab sessions and exercises.
  • Readings: Additional readings and reference materials.

Semester 1 📕

  • CL117 Intro to Info. and Comm. Technologies
  • CL118 Programming Fundamentals - Lab
  • CS118 Programming Fundamentals
  • EE117 Applied Physics
  • MT119 Calculus and Analytical Geometry
  • SL150 English Composition and Comprehension - Lab
  • SS111 Islamic and Religious Studies
  • SS150 English Composition and Comprehension

Semester 2 📗

  • CL217 Object Oriented Programming - Lab
  • CS217 Object Oriented Programming
  • EE227 Digital Logic Design
  • EL227 Digital Logic Design - Lab
  • MT224 Differential Equations (Cal II)
  • SL152 Communication & Presentation Skills - Lab
  • SS113 Pakistan Studies
  • SS152 Communication & Presentation Skills

Semester 3 📘

  • CL2001 Data Structures - Lab
  • CS1005 Discrete Structures
  • CS2001 Data Structures
  • DS2001 Introduction to Data Science
  • EE2003 Computer Organization and Assembly Language
  • EL2003 Computer Organization and Assembly Language- Lab
  • MT2005 Probability and Statistics

Semester 4 📙

  • CL2005 Database Systems - Lab
  • CS2004 Fundamentals of Software Engineering
  • CS2005 Database Systems
  • DL2004 Fundamental of Big Data Analytics - Lab
  • DS2003 Advanced Statistics
  • DS2004 Fundamental of Big Data Analytics
  • MT1004 Linear Algebra

Semester 5 📒

  • CL2006 Operating Systems - Lab
  • CS2006 Operating Systems
  • CS2009 Design and Analysis of Algorithms
  • DL3001 Data Analysis and Visualization - Lab
  • DS3001 Data Analysis and Visualization
  • DS3003 Data Warehousing and Business Intelligence
  • SS2007 Technical and Business Writing

Semester 6 📓

  • AI2002 Artificial Intelligence
  • AL2002 Artificial Intelligence - Lab
  • CS3006 Parallel and Distributed Computing
  • CS4051 Information Retrieval
  • DL3002 Data Mining - Lab
  • DS3002 Data Mining
  • MG4011 Entrepreneurship

Semester 7 📔

  • CL3001 Computer Networks - Lab
  • CS3001 Computer Networks
  • CS3002 Information Security
  • CS4001 Professional Practices in IT
  • CS4049 Blockchain and Cryptocurrency
  • DS4091 Final Year Project – I

Semester 8 📕

  • CS4032 Web Programming
  • CS4059 Fundamentals of Computer Vision
  • CS4063 Natural Language Processing
  • DS4092 Final Year Project – II
  • SS2036 Modern Politics and Government

How to Use This Repository 🛠️

  1. Navigate by Semester: Start by selecting the semester you are currently enrolled in or interested in. Each semester folder contains all relevant materials for the courses offered in that semester.

  2. Course-Specific Resources: Within each semester folder, you will find subdirectories for each course. These subdirectories contain:

    • Course Outlines: Review the course outlines to understand the scope, objectives, and structure of the course.
    • Notes: Use the lecture notes to study key concepts and reinforce your understanding.
    • Books: Access recommended textbooks for in-depth reading and comprehension.
    • Assignments: Practice with the provided assignments and refer to the solutions for self-assessment.
    • Lab Works: Complete the lab exercises to gain hands-on experience with practical applications.
    • Readings: Supplement your learning with additional readings and references.

  3. Search Functionality: Use the repository’s search functionality to quickly find specific topics, keywords, or files.

  4. Regular Updates: The repository will be updated periodically with new materials, solutions, and additional resources. Check back regularly to stay up-to-date.

Contribution Guidelines 🤝

If you have any additional resources, solutions, or improvements to share, please contribute to the repository:

  1. Fork the Repository: Create a fork of this repository to your GitHub account.
  2. Create a New Branch: Make a new branch for your contributions.
  3. Make Changes: Add your resources or improvements.
  4. Submit a Pull Request: Once your changes are complete, submit a pull request for review.

Contact 📬

If you have any questions, suggestions, or need further assistance, feel free to reach out:

Acknowledgements 🙏

I would like to thank my professors, classmates, and everyone who contributed to my learning journey at FAST NUCES. This repository is a collective effort to make learning more accessible and manageable for future students.

Happy Learning!📘

Fatima Azfar Data Science Graduate, FAST NUCES