Course Structure Overview
The Bachelor of Technology program at Mittal Institute of Technology is structured over 8 semesters, with a blend of core engineering courses, departmental electives, science electives, and laboratory sessions. Each semester carries a specific credit structure that aligns with industry standards and academic excellence.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| I | PH101 | Engineering Physics | 3-1-0-4 | None |
| I | CH101 | Engineering Chemistry | 3-1-0-4 | None |
| I | MA101 | Mathematics I | 4-0-0-4 | None |
| I | EC101 | Introduction to Electrical Engineering | 3-1-0-4 | None |
| I | CS101 | Programming and Problem Solving | 3-1-0-4 | None |
| I | HS101 | English for Communication | 3-0-0-3 | None |
| I | PH102 | Physics Lab | 0-0-2-2 | PH101 |
| I | CH102 | Chemistry Lab | 0-0-2-2 | CH101 |
| I | CS102 | Programming Lab | 0-0-2-2 | CS101 |
| II | MA201 | Mathematics II | 4-0-0-4 | MA101 |
| II | EC201 | Electrical Circuits and Networks | 3-1-0-4 | EC101 |
| II | PH201 | Thermodynamics | 3-1-0-4 | PH101 |
| II | CS201 | Data Structures and Algorithms | 3-1-0-4 | CS101 |
| II | CH201 | Organic Chemistry | 3-1-0-4 | CH101 |
| II | HS201 | Cultural Studies | 3-0-0-3 | None |
| II | EC202 | Electrical Circuits Lab | 0-0-2-2 | EC201 |
| II | CS202 | Data Structures Lab | 0-0-2-2 | CS201 |
| III | MA301 | Mathematics III | 4-0-0-4 | MA201 |
| III | EC301 | Digital Electronics | 3-1-0-4 | EC201 |
| III | PH301 | Fluid Mechanics | 3-1-0-4 | PH201 |
| III | CS301 | Object-Oriented Programming | 3-1-0-4 | CS201 |
| III | CH301 | Inorganic Chemistry | 3-1-0-4 | CH201 |
| III | HS301 | Professional Communication | 3-0-0-3 | HS201 |
| III | EC302 | Digital Electronics Lab | 0-0-2-2 | EC301 |
| III | CS302 | OOP Lab | 0-0-2-2 | CS301 |
| IV | MA401 | Mathematics IV | 4-0-0-4 | MA301 |
| IV | EC401 | Analog Electronics | 3-1-0-4 | EC301 |
| IV | PH401 | Heat Transfer | 3-1-0-4 | PH301 |
| IV | CS401 | Database Management Systems | 3-1-0-4 | CS301 |
| IV | CH401 | Physical Chemistry | 3-1-0-4 | CH301 |
| IV | HS401 | Ethics and Values | 3-0-0-3 | HS301 |
| IV | EC402 | Analog Electronics Lab | 0-0-2-2 | EC401 |
| IV | CS402 | DBMS Lab | 0-0-2-2 | CS401 |
| V | EC501 | Control Systems | 3-1-0-4 | EC401 |
| V | PH501 | Mechanics of Materials | 3-1-0-4 | PH401 |
| V | CS501 | Software Engineering | 3-1-0-4 | CS401 |
| V | CH501 | Biochemistry | 3-1-0-4 | CH401 |
| V | HS501 | Human Rights and Gender Studies | 3-0-0-3 | HS401 |
| V | EC502 | Control Systems Lab | 0-0-2-2 | EC501 |
| V | CS502 | Software Engineering Lab | 0-0-2-2 | CS501 |
| VI | EC601 | Signal Processing | 3-1-0-4 | EC501 |
| VI | PH601 | Electromagnetic Fields | 3-1-0-4 | PH501 |
| VI | CS601 | Machine Learning | 3-1-0-4 | CS501 |
| VI | CH601 | Environmental Chemistry | 3-1-0-4 | CH501 |
| VI | HS601 | Leadership and Management | 3-0-0-3 | HS501 |
| VI | EC602 | Signal Processing Lab | 0-0-2-2 | EC601 |
| VI | CS602 | ML Lab | 0-0-2-2 | CS601 |
| VII | EC701 | Antenna and Wave Propagation | 3-1-0-4 | EC601 |
| VII | PH701 | Structural Analysis | 3-1-0-4 | PH601 |
| VII | CS701 | Web Technologies | 3-1-0-4 | CS601 |
| VII | CH701 | Nanotechnology | 3-1-0-4 | CH601 |
| VII | HS701 | Entrepreneurship Development | 3-0-0-3 | HS601 |
| VII | EC702 | Antenna Lab | 0-0-2-2 | EC701 |
| VII | CS702 | Web Technologies Lab | 0-0-2-2 | CS701 |
| VIII | EC801 | Project Work | 4-0-0-4 | EC701 |
| VIII | PH801 | Final Thesis | 6-0-0-6 | PH701 |
| VIII | CS801 | Capstone Project | 4-0-0-4 | CS701 |
| VIII | CH801 | Final Research Project | 6-0-0-6 | CH701 |
| VIII | HS801 | Internship | 2-0-0-2 | HS701 |
Advanced Departmental Electives
Departmental electives offer students the opportunity to explore specialized areas within their chosen field. These courses are designed to align with industry trends and foster advanced technical skills.
Machine Learning (CS601)
This course introduces students to core concepts in machine learning, including supervised and unsupervised learning, neural networks, deep learning frameworks, and reinforcement learning. Students will implement algorithms using Python libraries such as TensorFlow and PyTorch.
Database Management Systems (CS401)
The course covers database design, normalization, SQL queries, transaction management, indexing strategies, and performance optimization. Students will gain hands-on experience with Oracle, MySQL, and PostgreSQL.
Signal Processing (EC601)
This advanced topic explores signal representation, filtering techniques, Fourier transforms, and digital signal processing applications in telecommunications and audio systems. Practical sessions involve MATLAB simulations and FPGA implementations.
Control Systems (EC501)
Students learn about mathematical modeling, stability analysis, feedback control systems, and PID controllers. The course includes laboratory experiments using Simulink and hardware-based control units.
Software Engineering (CS501)
This course covers software development life cycle, agile methodologies, testing strategies, version control systems, and project management tools like JIRA and Confluence.
Web Technologies (CS701)
The curriculum includes HTML/CSS, JavaScript frameworks, RESTful APIs, database integration, and cloud deployment services. Students will build full-stack web applications using React, Node.js, and MongoDB.
Electromagnetic Fields (PH601)
This course delves into Maxwell's equations, wave propagation, transmission lines, and antenna theory. Labs involve electromagnetic field measurements and simulation software like CST Studio Suite.
Environmental Chemistry (CH601)
The subject covers environmental pollutants, green chemistry principles, biodegradation processes, and sustainable chemical manufacturing techniques. Students will conduct laboratory experiments related to water and air quality analysis.
Structural Analysis (PH701)
This course focuses on structural mechanics, load analysis, beam theory, truss systems, and finite element modeling. Labs involve structural testing using software like SAP2000 and STAAD.Pro.
Data Science and Analytics (CS601)
Students learn data cleaning, statistical modeling, visualization tools, predictive analytics, and machine learning applications in business intelligence. Tools covered include Pandas, Scikit-learn, and Tableau.
Project-Based Learning Philosophy
Mittal Institute of Technology strongly emphasizes project-based learning as a cornerstone of engineering education. Projects are designed to simulate real-world challenges and encourage innovation.
Mini-Projects
Mini-projects begin in the second year and continue through the third year. Students select topics based on their interests and receive guidance from faculty mentors. These projects typically last 6–8 weeks and culminate in presentations to industry experts.
Final-Year Thesis/Capstone Project
The final-year project is a comprehensive endeavor that integrates knowledge from all previous semesters. Students work closely with faculty advisors on original research or applied engineering problems. The thesis must be defended in front of a committee comprising internal and external evaluators.
Project Selection Process
Students choose their projects through an online portal where they can review available topics, mentor profiles, and past project reports. Faculty members also propose research directions aligned with current industry needs.
Evaluation Criteria
Projects are evaluated based on technical depth, innovation, presentation quality, teamwork, and documentation standards. A rubric is provided to ensure transparency and consistency in grading.