Course Structure Overview
The engineering program at I E S University Bhopal is designed to provide a comprehensive understanding of engineering principles, followed by specialized knowledge in chosen disciplines. The curriculum spans 8 semesters and includes core subjects, departmental electives, science electives, and laboratory sessions that are essential for practical application.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | ENG102 | Physics for Engineers | 3-1-0-4 | - |
| 1 | ENG103 | Chemistry and Biology | 3-1-0-4 | - |
| 1 | ENG104 | Introduction to Engineering | 2-0-2-3 | - |
| 1 | ENG105 | English for Engineers | 2-0-0-2 | - |
| 1 | ENG106 | Computer Programming Lab | 0-0-3-2 | - |
| 2 | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | ENG202 | Electrical Engineering Fundamentals | 3-1-0-4 | - |
| 2 | ENG203 | Mechanics of Materials | 3-1-0-4 | - |
| 2 | ENG204 | Engineering Drawing | 2-0-2-3 | - |
| 2 | ENG205 | Environmental Science | 2-1-0-3 | - |
| 2 | ENG206 | Digital Logic Lab | 0-0-3-2 | - |
| 3 | ENG301 | Thermodynamics | 3-1-0-4 | ENG201 |
| 3 | ENG302 | Fluid Mechanics | 3-1-0-4 | - |
| 3 | ENG303 | Materials Science | 3-1-0-4 | - |
| 3 | ENG304 | Electromagnetic Fields | 3-1-0-4 | - |
| 3 | ENG305 | Engineering Ethics | 2-0-0-2 | - |
| 3 | ENG306 | Signals and Systems Lab | 0-0-3-2 | - |
| 4 | ENG401 | Control Systems | 3-1-0-4 | ENG301 |
| 4 | ENG402 | Design and Analysis of Algorithms | 3-1-0-4 | - |
| 4 | ENG403 | Probability and Statistics | 3-1-0-4 | - |
| 4 | ENG404 | Software Engineering | 3-1-0-4 | - |
| 4 | ENG405 | Computer Architecture | 3-1-0-4 | - |
| 4 | ENG406 | Microprocessors Lab | 0-0-3-2 | - |
| 5 | ENG501 | Machine Learning | 3-1-0-4 | ENG402 |
| 5 | ENG502 | Cybersecurity Fundamentals | 3-1-0-4 | - |
| 5 | ENG503 | Renewable Energy Technologies | 3-1-0-4 | - |
| 5 | ENG504 | Advanced Data Structures | 3-1-0-4 | - |
| 5 | ENG505 | Embedded Systems Design | 3-1-0-4 | - |
| 5 | ENG506 | Neural Networks Lab | 0-0-3-2 | - |
| 6 | ENG601 | Advanced Control Systems | 3-1-0-4 | ENG401 |
| 6 | ENG602 | Software Testing and Quality Assurance | 3-1-0-4 | - |
| 6 | ENG603 | Industrial Automation | 3-1-0-4 | - |
| 6 | ENG604 | Research Methodology | 2-1-0-3 | - |
| 6 | ENG605 | Robotics and AI | 3-1-0-4 | - |
| 6 | ENG606 | Capstone Project Lab | 0-0-6-4 | - |
| 7 | ENG701 | Project Management | 2-1-0-3 | - |
| 7 | ENG702 | Advanced Topics in AI | 3-1-0-4 | - |
| 7 | ENG703 | Big Data Analytics | 3-1-0-4 | - |
| 7 | ENG704 | Internet of Things | 3-1-0-4 | - |
| 7 | ENG705 | Advanced Cybersecurity | 3-1-0-4 | - |
| 7 | ENG706 | Research Project | 0-0-6-6 | - |
| 8 | ENG801 | Final Year Thesis | 0-0-9-12 | - |
Advanced Departmental Elective Courses
Departmental electives in the engineering program are carefully curated to reflect current industry trends and research frontiers. These courses offer specialized knowledge and practical skills that enhance employability and prepare students for advanced roles.
Machine Learning
This course introduces advanced machine learning techniques, including deep learning architectures, neural networks, and reinforcement learning. Students will gain hands-on experience using frameworks like TensorFlow and PyTorch to build predictive models and solve complex problems in various domains.
Cybersecurity Fundamentals
The course covers essential cybersecurity concepts, including network security, cryptography, system vulnerabilities, and ethical hacking. Through simulations and real-world case studies, students will learn how to protect digital assets and respond effectively to cyber threats.
Renewable Energy Technologies
This course explores the design, implementation, and optimization of renewable energy systems such as solar panels, wind turbines, and hydroelectric plants. Students will study environmental impacts, economic feasibility, and policy frameworks influencing clean energy adoption.
Advanced Data Structures
This course delves into advanced data structures beyond basic arrays and linked lists, covering trees, graphs, heaps, hash tables, and their applications in algorithm design and problem-solving. It emphasizes performance optimization techniques and real-world implementations.
Embedded Systems Design
Students will explore the architecture, programming, and application development of embedded systems. The course includes hands-on projects using microcontrollers, sensors, and real-time operating systems to build functional embedded applications.
Neural Networks Lab
This laboratory-based course provides extensive practice in designing, training, and evaluating neural networks. Students will work with datasets from various fields, apply different architectures, and analyze model performance using visualization tools.
Advanced Control Systems
The course extends foundational control theory to advanced topics such as state-space representation, optimal control, and robust control. Practical applications include robotics, process control, and aerospace systems.
Software Testing and Quality Assurance
This course focuses on software testing methodologies, quality assurance practices, and test automation tools. Students will develop comprehensive testing strategies, execute tests across different levels, and ensure product reliability and user satisfaction.
Industrial Automation
The course introduces industrial automation technologies including programmable logic controllers (PLCs), SCADA systems, and sensor integration. Students will learn to design automated solutions for manufacturing environments.
Research Methodology
This course provides a framework for conducting independent research in engineering disciplines. Topics include hypothesis formulation, experimental design, data analysis, literature review, and academic writing.
Robotics and AI
The course combines robotics engineering with artificial intelligence to create intelligent robotic systems. Students will learn robot kinematics, sensor integration, motion planning, and machine learning applications in robotics.
Project-Based Learning Philosophy
I E S University Bhopal strongly believes in project-based learning as a means to develop critical thinking and practical skills. Mini-projects are integrated throughout the curriculum to reinforce theoretical concepts and encourage innovation.
The structure of these projects involves selecting a topic aligned with personal interests or industry needs, conducting literature research, designing solutions, implementing prototypes, and presenting findings. Evaluation criteria include technical accuracy, creativity, teamwork, presentation quality, and adherence to deadlines.
Final-year thesis/capstone projects are more comprehensive, involving extensive research, design, implementation, and documentation. Students collaborate closely with faculty mentors who guide them through the research process, ensuring academic rigor and professional development.
Students can choose projects from a list provided by faculty or propose their own ideas after consultation with mentors. This flexibility encourages individuality and allows students to pursue areas of personal interest while meeting academic requirements.