Study Materials


Introduction

Welcome to the Study Materials Repository. Here, you'll find notes and resources for various subjects across different semesters. Use the table of contents in the dropdown menu to navigate through the subjects by semester.

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1 Semester


Engineering Mathematics I

Mathematical foundations and techniques for engineering problems.

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Environmental Science

Study of the environment and how to protect it.

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Foundations of Electronics Engineering

Basics of electronics engineering and its applications.

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Fundamentals of Computational Biology

Introduction to computational techniques in biology.

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Language and Writing Skills

Developing proficiency in language and writing.

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Learning Programming Concepts With C

Introduction to programming concepts using the C language.

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Professional Ethics and Life Skills

Understanding professional ethics and developing life skills.

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2 Semester


Data Structure Using C

Data structures and algorithms using the C language.

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Digital Logic and Design

Principles of digital logic and circuit design.

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Engineering Mathematics II

Advanced mathematical techniques for engineering problems.

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Entrepreneurship

Basics of entrepreneurship and startup management.

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Object-Oriented Programming

Principles and techniques of object-oriented programming.

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Python For Datascience

Introduction to data science using Python.

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3 Semester


Analysis and Design of Algorithm

Techniques for analyzing and designing algorithms.

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Computer Organization and Architecture

Fundamentals of computer organization and architecture.

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Database Management System

Principles of database management and SQL.

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Discrete Structure

Fundamentals of discrete mathematics and structures.

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Probability and Statistics

Introduction to probability theory and statistical methods for data analysis.

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Independent Project

Exploring new ideas and developing innovative projects independently.

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4 Semester


Artificial Intelligence Principles and Applications

Introduction to artificial intelligence concepts and techniques.

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Computer Network

Study of computer network architectures and protocols.

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Data Visualization

Techniques and tools for data visualization.

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Operating System

Concepts and principles of operating systems.

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R for Data Science

Data analysis and visualization using the R programming language.

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Theory of Computation

Study of computational systems, automata, and formal languages.

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5 Semester


Computational Complexity

Analysis of algorithm efficiency and classification of computational problems.

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Cryptography and Network Security

Fundamentals of cyber security and information protection.

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Intelligent Data Analysis

Techniques for extracting meaningful insights from complex data sets.

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Natural Language Processing

Computational techniques for analyzing and understanding human language.

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Pattern Recognition and Machine Learning

Study of machine learning concepts and algorithms.

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Vocational Training

Practical skills and training for specific trades and professions.

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6 Semester


Internship

Developing professional skills and gaining industry experience.

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