Courses

These sessions aim to bridge the gap between academic learning and industry expectations.

Students gain practical insights, motivation, and clarity to make informed career decisions.

An initiative to inspire, mentor, and prepare students for a successful professional journey.

Course Overview

This course provides a rigorous introduction to Python programming, tailored for the technical rigor expected at IGIT Sarang. It is designed to take students from the fundamental building blocks of programming to the application of standard libraries for engineering problem-solving. By learning directly from IGIT professors, students ensure their technical skills align perfectly with both academic requirements and industry standards.

OOPs Using C++ introduces students to the principles of object-oriented software development using the C++ programming language. The subject focuses on designing programs using concepts such as classes, objects, encapsulation, inheritance, polymorphism, and abstraction. It also covers constructors, destructors, operator overloading, templates, and basic exception handling to build efficient, reusable, and maintainable applications.

This course helps students develop strong problem-solving skills and prepares them for real-world software development and advanced programming concepts.

The Operating System course introduces the fundamental concepts and functions of modern operating systems. It explains how an operating system acts as an interface between users and computer hardware while efficiently managing system resources.

This course covers essential topics such as process management, CPU scheduling, memory management, file systems, device management, and disk management. Students will learn how operating systems coordinate hardware and software, ensure system security, and provide a stable and efficient computing environment.

By the end of the course, learners will gain a strong understanding of how operating systems work internally and how they support application execution and system performance in real-world computing systems.

The Database Management System (DBMS) course provides a comprehensive understanding of how data is stored, organized, managed, and retrieved efficiently in computer systems. It introduces the concepts of databases, database models, and the role of DBMS in modern information systems.

This course covers topics such as data models, entity–relationship modeling, relational databases, SQL, normalization, transaction management, concurrency control, and recovery techniques. Students will learn how databases ensure data consistency, security, and integrity while supporting multiple users.

By the end of the course, learners will be able to design databases, write SQL queries, manage transactions, and understand how DBMS supports real-world applications such as banking, education, and enterprise systems.

The Design of Algorithms with Data Structures course aims to develop strong analytical and problem-solving skills by teaching students how to design efficient algorithms using appropriate data structures. The course emphasizes understanding algorithm behavior, performance analysis, and practical implementation.

It covers algorithm analysis (time and space complexity), arrays, stacks, queues, linked lists, trees, graphs, sorting and searching techniques, hashing, greedy algorithms, divide-and-conquer strategies, dynamic programming, and graph algorithms. Students learn how to choose optimal data structures to improve program efficiency.

By the end of the course, learners will be able to analyze algorithm efficiency, design optimized solutions, and apply data structures effectively to solve real-world computational problems.

The Formal Languages and Automata Theory course introduces the mathematical foundations of computation and language processing. It focuses on the study of formal languages, grammars, and abstract machines that recognize and generate languages.

This course covers finite automata, regular expressions, regular languages, context-free grammars, pushdown automata, Turing machines, decidability, and computational complexity. Students will understand how different computational models work and their limitations.

By the end of the course, learners will be able to analyze language structures, design automata for pattern recognition, and understand the theoretical basis of compilers, interpreters, and programming languages.