Search and navigate to colleges and courses
Apply
Scholarships & exams
Fees
₹1,50,000
Placement
94.5%
Avg Package
₹6,50,000
Highest Package
₹9,50,000
Fees
₹1,50,000
Placement
94.5%
Avg Package
₹6,50,000
Highest Package
₹9,50,000
Seats
120
Students
800
Seats
120
Students
800
The engineering curriculum at Pragjyotishpur University Kamrup is meticulously designed to provide students with a robust foundation in core engineering principles while offering flexibility for specialization and innovation. The program spans four years and 8 semesters, integrating theoretical knowledge with practical application through hands-on laboratory sessions, industry projects, and research opportunities.
The first year focuses on building strong fundamentals in mathematics, physics, chemistry, and basic engineering concepts. Students are introduced to problem-solving techniques, critical thinking skills, and the principles of engineering design. This foundational year ensures that all students have a common base of knowledge before progressing to specialized subjects.
The second year delves deeper into core engineering disciplines including electrical circuits, mechanics, thermodynamics, fluid mechanics, and materials science. Students also begin exploring departmental electives that allow them to discover their areas of interest and align their academic pursuits with career goals.
The third year introduces advanced topics in the chosen specialization track while maintaining a strong focus on practical application through industry internships, research projects, and collaborative work. Students develop specialized skills that prepare them for either direct employment or further academic pursuits.
The final year emphasizes capstone projects and independent research, where students apply their knowledge to solve real-world problems under the guidance of experienced faculty mentors. This culminating experience often leads to publications, patent applications, or startup ventures, ensuring that graduates are well-prepared for professional success.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PHYS101 | Physics for Engineers | 3-1-0-4 | - |
| 1 | MATH101 | Mathematics I | 4-0-0-4 | - |
| 1 | CHM101 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | EG101 | Engineering Graphics | 2-1-0-3 | - |
| 1 | EC101 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | ME101 | Introduction to Mechanical Engineering | 2-0-0-2 | - |
| 1 | CS101 | Introduction to Programming | 3-0-2-5 | - |
| 1 | ENG101 | English for Engineers | 2-0-0-2 | - |
| 1 | SS101 | Social Sciences and Humanities | 2-0-0-2 | - |
| 2 | MATH102 | Mathematics II | 4-0-0-4 | MATH101 |
| 2 | PHYS102 | Physics II | 3-1-0-4 | PHYS101 |
| 2 | CIV101 | Introduction to Civil Engineering | 2-0-0-2 | - |
| 2 | EC102 | Electronics Devices and Circuits | 3-1-0-4 | EC101 |
| 2 | ME102 | Mechanics of Materials | 3-1-0-4 | ME101 |
| 2 | CS102 | Data Structures and Algorithms | 3-0-2-5 | CS101 |
| 2 | ME103 | Thermodynamics | 3-1-0-4 | ME101 |
| 2 | SS102 | Professional Ethics and Values | 2-0-0-2 | - |
| 3 | MATH201 | Mathematics III | 4-0-0-4 | MATH102 |
| 3 | PHYS201 | Physics III | 3-1-0-4 | PHYS102 |
| 3 | EC201 | Digital Electronics and Logic Design | 3-1-0-4 | EC102 |
| 3 | ME201 | Fluid Mechanics | 3-1-0-4 | ME102 |
| 3 | CS201 | Database Management Systems | 3-0-2-5 | CS102 |
| 3 | CIV201 | Strength of Materials | 3-1-0-4 | CIV101 |
| 3 | ME202 | Mechanical Vibrations | 3-1-0-4 | ME103 |
| 3 | SS201 | Environmental Studies | 2-0-0-2 | - |
| 4 | MATH202 | Mathematics IV | 4-0-0-4 | MATH201 |
| 4 | PHYS202 | Physics IV | 3-1-0-4 | PHYS201 |
| 4 | EC202 | Signals and Systems | 3-1-0-4 | EC201 |
| 4 | ME203 | Heat Transfer | 3-1-0-4 | ME201 |
| 4 | CS202 | Computer Networks | 3-0-2-5 | CS201 |
| 4 | CIV202 | Structural Analysis | 3-1-0-4 | CIV201 |
| 4 | ME204 | Mechanical Design | 3-1-0-4 | ME202 |
| 4 | SS202 | Entrepreneurship and Innovation | 2-0-0-2 | - |
| 5 | EC301 | Control Systems | 3-1-0-4 | EC202 |
| 5 | ME301 | Advanced Thermodynamics | 3-1-0-4 | ME203 |
| 5 | CS301 | Artificial Intelligence and Machine Learning | 3-0-2-5 | CS202 |
| 5 | CIV301 | Foundation Engineering | 3-1-0-4 | CIV202 |
| 5 | ME302 | Manufacturing Processes | 3-1-0-4 | ME204 |
| 5 | SS301 | Project Management | 2-0-0-2 | - |
| 6 | EC302 | Communication Systems | 3-1-0-4 | EC301 |
| 6 | ME303 | Advanced Materials | 3-1-0-4 | ME301 |
| 6 | CS302 | Software Engineering | 3-0-2-5 | CS301 |
| 6 | CIV302 | Transportation Engineering | 3-1-0-4 | CIV301 |
| 6 | ME304 | Refrigeration and Air Conditioning | 3-1-0-4 | ME302 |
| 6 | SS302 | Globalization and Its Impact | 2-0-0-2 | - |
| 7 | EC401 | Embedded Systems | 3-1-0-4 | EC302 |
| 7 | ME401 | Finite Element Analysis | 3-1-0-4 | ME303 |
| 7 | CS401 | Big Data Analytics | 3-0-2-5 | CS302 |
| 7 | CIV401 | Water Resources Engineering | 3-1-0-4 | CIV302 |
| 7 | ME402 | Robotics and Automation | 3-1-0-4 | ME304 |
| 7 | SS401 | Sustainable Development | 2-0-0-2 | - |
| 8 | EC402 | Advanced Communication Techniques | 3-1-0-4 | EC401 |
| 8 | ME403 | Advanced Manufacturing | 3-1-0-4 | ME401 |
| 8 | CS402 | Cybersecurity and Network Security | 3-0-2-5 | CS401 |
| 8 | CIV402 | Geotechnical Engineering | 3-1-0-4 | CIV401 |
| 8 | ME404 | Energy Systems | 3-1-0-4 | ME402 |
| 8 | SS402 | Leadership and Management | 2-0-0-2 | - |
Departmental electives form a crucial part of the engineering curriculum, allowing students to specialize in areas of particular interest while maintaining a strong foundation in core principles. These courses are designed to provide depth and practical application of advanced concepts.
This course provides students with comprehensive knowledge of AI and ML techniques, including neural networks, deep learning, natural language processing, and computer vision. Students develop practical skills through hands-on projects using industry-standard tools like TensorFlow, PyTorch, and scikit-learn.
The learning objectives include understanding fundamental concepts of machine learning algorithms, implementing neural networks for pattern recognition, and applying AI techniques to real-world problems in healthcare, finance, and autonomous systems.
This course focuses on the systematic approach to software development, covering software architecture, testing methodologies, project management, and quality assurance. Students learn agile development practices and work on collaborative projects that simulate real-world software development environments.
Learning outcomes include designing scalable software systems, applying software testing techniques, managing software projects effectively, and understanding the lifecycle of software products from inception to deployment.
This advanced course addresses modern cybersecurity challenges including network security protocols, cryptography, ethical hacking, and incident response. Students gain practical experience through simulation environments and real-world case studies.
The curriculum covers network vulnerabilities, security frameworks, penetration testing techniques, and the development of secure software applications in response to evolving cyber threats.
This course explores the principles and techniques of handling large datasets using modern analytics tools and methods. Students learn data mining, statistical analysis, and visualization techniques while working with real-world datasets from various domains.
Learning objectives include understanding big data technologies, applying analytical methods to extract insights from complex datasets, and developing skills in data-driven decision making for business applications.
This course delves into the structure-property relationships of advanced materials including composites, nanomaterials, and smart materials. Students study material processing techniques, characterization methods, and applications in modern engineering systems.
The course emphasizes practical applications in aerospace, automotive, and biomedical industries where advanced materials play a critical role in performance optimization.
This advanced course teaches the principles of finite element methods for solving complex engineering problems. Students learn to model physical systems using computational tools and analyze stress, strain, and other mechanical behaviors.
Learning outcomes include understanding numerical methods for engineering analysis, applying FEM software tools effectively, and interpreting results in the context of real-world engineering challenges.
This course focuses on designing and implementing systems that integrate computing capabilities with physical environments. Students learn microcontroller programming, sensor integration, and real-time system design principles.
The curriculum covers both hardware and software aspects of embedded systems development, preparing students for careers in IoT, automotive electronics, and industrial automation sectors.
This course explores modern communication technologies including wireless systems, signal processing, and network protocols. Students gain hands-on experience with communication equipment and simulation tools.
Learning objectives include understanding communication system design principles, analyzing signal transmission methods, and applying advanced techniques for improving communication efficiency and reliability.
This course addresses the design and optimization of energy conversion systems including renewable energy technologies, power generation, and energy storage solutions. Students study both conventional and emerging energy systems.
The curriculum emphasizes sustainable energy solutions and practical applications in addressing global energy challenges through innovative engineering approaches.
This advanced course covers the principles of soil mechanics, foundation design, and geotechnical analysis. Students learn to assess ground conditions and design stable structures for various construction environments.
Learning outcomes include understanding soil behavior under different loading conditions, applying geotechnical analysis methods, and designing safe and efficient foundation systems for civil engineering projects.
Pragjyotishpur University Kamrup's engineering program embraces a strong project-based learning approach that emphasizes hands-on experience and real-world problem-solving. This philosophy recognizes that effective learning occurs when students engage with practical challenges that mirror industry requirements.
The curriculum integrates project work throughout all four years, starting with small-scale laboratory projects in the first year and progressing to complex, multi-disciplinary capstone projects in the final year. This approach ensures that students develop both technical expertise and professional skills simultaneously.
Mini-projects are assigned during the second and third years, providing students with opportunities to apply theoretical concepts to practical situations. These projects typically span 2-3 months and involve teams of 3-5 students working under faculty mentorship.
The evaluation criteria for mini-projects include technical correctness, innovation in approach, presentation quality, and teamwork effectiveness. Students must document their work through detailed project reports and present findings to faculty and peers.
The final-year capstone project represents the culmination of students' engineering education. These projects are typically undertaken in collaboration with industry partners or research organizations, providing students with exposure to real-world challenges and professional environments.
Students work under the guidance of faculty mentors who provide technical expertise and career advice throughout the project lifecycle. The evaluation process includes progress reports, mid-term presentations, and final defense sessions where students demonstrate their solutions to a panel of experts.
The capstone project experience prepares students for careers in industry or further academic pursuits by developing skills in problem identification, research methodology, technical communication, and professional presentation.
