BTech Robotics and Automation
An industry relevant course to chart your journey in Industry 4.0
Why needed?
The B.Tech in Robotics & Automation at NIIT University (NU) is an interdisciplinary programme designed to prepare students for the rapidly evolving world of intelligent machines and automation. It integrates mechanical engineering, electronics, computer science, and artificial intelligence to create a new generation of engineers who can design, build, and manage autonomous systems across industries.
Students gain hands-on experience through project-based learning, state-of-the-art laboratories, and industry collaborations with leading automation companies. The curriculum covers robotics design, control systems, embedded programming, machine vision, and AI-driven automation, ensuring a strong foundation in both theory and real-world applications.
Through partnerships with industry leaders such as Addverb Technologies, students participate in internships, live projects, and co-created courses that bridge academic knowledge with workplace needs. The programme emphasizes innovation, problem-solving, and ethical technology development — preparing graduates for diverse roles in robotics, manufacturing, logistics, industry automation, and smart infrastructure.
NIIT University introduces flexible curricular architecture through Industry Practice and Research Practice
In keeping with NU’s Core Principle of Industry-linked, BTech Robotics and Automation students undertake a compulsory six-month Industry Practice (IP) at the industry site and are jointly supervised by industry and faculty mentors.
Industry Practice (IP) has been widely appreciated by NU’s industry partners with a majority of students been given a pre-placement offer (PPO). Industry organisations have also expressed interest in longer duration IP.
Further NEP 2020 (National Education Policy 2020) too actively encourages internships with industry to improve employability of students. It also suggests offering research internship opportunities with faculty researchers in own institution or other institutions and research organisations. This has been reflected in UGC and AICTE policy and guidelines.
With this in mind, NU provides undergraduate students with three curricular architectures, including a revolutionary 1-Year Research Practice in the place of a single fixed architecture. This gives flexibility to students to craft their own industry/research engagement keeping their preference and motivation by choosing any one of the three curricular architectures.
The three curricular architectures are as follows:
- Curricular architecture 1: 6-month Industry Practice in the final eighth semester
- Curricular architecture 2: 1-Year Industry Practice spreading across two semesters in the final year
- Curricular architecture 3: 1-Year Research Practice spreading across two semesters in the final year
BTech Robotics and Automation – Distinguishing Features
Like all our other flagship programmes, the BTech Robotics and Automation course is designed around NU’s core principles of providing industry-linked, technology-based, research-driven and seamless education.
Our BTech Robotics and Automation programme places you on a high-growth career journey that is both rewarding and fulfilling. Here’s how:
Industry-linked course architecture/curriculum
The curriculum and architecture aim to provide students dual advantages of academic rigor and real-world industry experiences. The curriculum has been developed with inputs from industry experts and faculty researchers. Students work and interact with industry and research institutions from the first year itself.
Industry-academic synergy for real-life immersive learning
The programme provides a comprehensive and immersive learning experience. Students choosing the 6-month Industry Practice track will complete one capstone project, undertake an R&D (Research and Development) project, and have the option to further deepen their work through an Advanced R&D project.
Students opting for the 1-Year Industry Practice or Research Practice track will undertake an R&D project, with the opportunity to extend it into an Advanced R&D project, while engaging in Industry Practice or Research Practice during the final two semesters.
Top-notch faculty
Our Robotics & Automation faculty bring together deep academic expertise and extensive industry experience, creating a powerful blend of theory and practice. With strong research credentials, publications in reputed international journals and conferences, and active involvement in cutting-edge domains such as intelligent robotics, autonomous systems, control engineering, computer vision, AI-driven automation, and Industry 4.0, they mentor students to think innovatively and solve real-world problems. Their commitment to hands-on learning, interdisciplinary research, industry collaboration, and outcome-oriented mentoring ensures that students graduate as highly skilled, future-ready professionals in Robotics & Automation.
State-of-the-art infrastructure
True to its core principle of Technology-based, NU offers high-tech laboratories with all the necessary software and equipment to assist students in their experiential learning journey.
Unique teaching methodology
Several unique teaching methods are integrated into the project-based learning approach at NU. This approach helps students to develop critical thinking skills to engage deeply with subjects, interdisciplinary skills to see connections between subjects, collaborative skills to work as a team to solve a real-life problem. They become independent and self-directed learners who can chart their own learning journey successfully.
Programme outcomes
NU’s undergraduate programmes in Engineering and Management are designed to provide thorough grounding in the respective disciplines, offer a course of work that prepares them for either a professional career or advanced degrees.
NU expects that graduates of the undergraduate Engineering programmes will demonstrate the following programme outcomes as defined by NBA (National Board of Accreditation).
PO1
Engineering knowledge
Apply the knowledge of Mathematics, Science, fundamentals of Engineering and an engineering specialisation to the solution of complex engineering problems.
PO2
Problem analysis
Identify, formulate, review research literature, and analyse complex engineering problems to reach substantiated conclusions using first principles of Mathematics, Natural Sciences, and Engineering Sciences.
PO3
Design/Develop solutions
Design solutions for complex engineering problems and system components or processes that meet specified needs with appropriate consideration for public health and safety, and cognisant of cultural, societal, and environmental considerations.
PO4
Conduct investigations of complex problems
Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesise information to provide valid conclusions.
PO5
Modern tool usage
Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
PO6
The engineer and society
Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues, and the consequent responsibilities relevant to the professional engineering practice.
PO7
Environment and sustainability
Understand the impact of professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO8
Ethics
Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9
Individual and teamwork
Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO10
Communication
Communicate effectively on complex engineering activities with the engineering community and with society at large. This includes being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PO11
Project management and finance
Demonstrate knowledge and understanding of engineering and management principles and apply these to one’s own work, as a member and/or leader in a team, to manage projects in multidisciplinary environments.
PO12
Life-long learning
Recognise the need for, and have the preparation and ability to, engage in independent and life-long learning in the broadest context of technological change.
PSOs for BTech Robotics and Automation
Graduates of the BTech Robotics and Automation programme will be able to:
PSO1
Apply knowledge of mechanical, electrical, electronics, and computer science fundamentals to model, design, and control robotic systems.
PSO2
Analyze, design, and implement automation solutions by integrating sensors, actuators, controllers, and intelligent algorithms.
PSO3
Develop and deploy robotic and automation systems using modern software tools, programming platforms, and simulation environments.
PSO4
Apply robotics and automation principles to interdisciplinary domains such as manufacturing, agriculture, healthcare, and autonomous systems, ensuring sustainability and safety.
PSO5
Communicate technical concepts effectively and work collaboratively in multidisciplinary teams to solve complex engineering problems and innovate new robotic solutions.
| Course category | Credits* |
|---|---|
| Basic Sciences | 20 |
| Engineering Sciences | 09 |
| Professional compulsory | 105 |
| Industry Practice | 20 |
| Open Electives | 12 |
| Humanities and Social Sciences / Activity Oriented Courses | 15 |
| Total credits | 181 |
* For 6-month Industry Practice
- Microprocessor & Microcontroller
- Basic Mechanical Engineering
- Programming for Robotics
- Signals & Systems
- IOT and Sensor Networks
- Mechatronics Systems Design
- Digital Image Processing
- Advanced Embedded Systems
- Introduction to Linear and Nonlinear Optimization
- Control Theory
- Computer Vision
- Artificial Intelligence
- Machine Learning
- Kinematics of the Robotics
- Database Systems & Cloud Integration
- Robotics Systems Integration
- Industrial Control Robotics and Automation
- Deep Learning and Generative AI
- Advanced IoT & Edge Computing
- Power Electronics and Instrumentation
- Autonomous Systems
- Advanced Embedded Systems
- Advanced Digital Signal Processing
- Wireless Broadband Communications
- Architecture Protocols and Design Principles of IoT
- IOT and Sensor Networks
- Industrial control robotics and Automation
- Real Time Operating System
- Kinematics of Robotics
- Artificial Intelligence
- Machine Learning
- Neural Networks and Deep Learning
- Non-Linear Optical Communication
- Satellite Communications
- Advanced VLSI
- Internet of Things
- Computer Vision
- Power Electronics
- Radar Engineering
- Cellular and Mobile Communications
- Advanced Wireless Broadband Communications
- Artificial Intelligence
- Artificial Neural Networks
- Statistical Modeling for Data Science
- Wireless Sensor Networks and Applications
- Machine Learning
- Computational Geometry and Applications
- Cyber Security
- Data Mining
- Introduction to Information Security
- Natural Language Processing
B Tech Robotics and Automation course architecture – subjects & syllabus with 6-month Industry Practice
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| MAT 112 | Calculus | 3 | 1 | 0 | 4 |
| EL 111 | Fundamentals of Electronics | 3 | 0 | 2 | 4 |
| Science I | 3 | 0 | 3 | 4 | |
| TA 111 | Fundamentals of Computer Programming | 2 | 0 | 4 | 4 |
| TA 202 | Engineering Graphics/ Workshop Practice | 2 | 0 | 2 | 3 |
| TA 212 | 1 | 0 | 4 | 3 | |
| TA 102 | Communication Skills/HSSM-I | 2 | 0 | 2 | 3 |
| 3 | 0 | 0 | 3 | ||
| NU 111 | Community Connect | 0 | 0 | 2 | 1 |
| Total semester L-T-P-C | 15 | 1 | 10 | 22 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| MAT 101 | Algebra & Differential Equation | 3 | 1 | 0 | 4 |
| Science II | 3 | 0 | 3 | 4 | |
| EL 101 | Digital Logic and Circuit | 3 | 0 | 2 | 3 |
| CS 102 | Data Structures | 3 | 0 | 2 | 4 |
| TA 202 | Engineering Graphics / Workshop Practice | 2 | 0 | 2 | 3 |
| TA 212 | 1 | 0 | 4 | 3 | |
| TA 102 | Communication Skills / HSSM-I | 2 | 0 | 2 | 3 |
| 3 | 0 | 0 | 3 | ||
| NU 112 | Community Connect | 0 | 0 | 2 | 1 |
| Total semester L-T-P-C | 16 | 1 | 10 | 22 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| MAT 221 | Probability & Random Process | 3 | 1 | 0 | 4 |
| EL 202 | Microprocessor & Microcontroller | 3 | 0 | 2 | 4 |
| ME 201 | Basic Mechanical Engineering | 3 | 1 | 0 | 4 |
| CS 2111 | Programming for Robotics | 2 | 0 | 4 | 4 |
| EL 211 | Signals & Systems | 3 | 1 | 0 | 4 |
| EL 332 | IOT and Sensor Networks | 3 | 0 | 2 | 4 |
| Total semester L-T-P-C | 17 | 3 | 8 | 24 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| ME 202 | Mechatronics Systems Design | 3 | 0 | 2 | 4 |
| EL 302 | Digital Image Processing | 3 | 0 | 2 | 4 |
| EL 312 | Advanced Embedded Systems | 3 | 0 | 2 | 4 |
| CS 4101 | Introduction to Linear and Nonlinear Optimization | 3 | 0 | 2 | 4 |
| EC 302 | Control Theory | 3 | 0 | 2 | 4 |
| HSSM-II | 3 | 0 | 0 | 3 | |
| Total semester L-T-P-C | 18 | 0 | 10 | 23 |
| Course Code | Course Title | L | T | P | C |
|---|---|---|---|---|---|
| CS 4111 | Computer Vision | 3 | 0 | 2 | 4 |
| CS 322 | Artificial Intelligence | 3 | 0 | 2 | 4 |
| CS 4131 | Machine Learning | 3 | 0 | 2 | 4 |
| EL 362 | Kinematics of the Robotics | 3 | 0 | 2 | 4 |
| CS 3101 | Database Systems & Cloud Integration | 3 | 0 | 2 | 4 |
| HSSM-III | 3 | 0 | 0 | 3 | |
| Total Semester L-T-P-C | 18 | 0 | 10 | 23 |
| Course Code | Course Title | L | T | P | C |
|---|---|---|---|---|---|
| EL 382 | Robotics Systems Integration | 3 | 0 | 2 | 4 |
| EL 322 | Industrial Control Robotics and Automation | 3 | 0 | 2 | 4 |
| CS 4341 | Deep Learning and Generative AI | 3 | 0 | 2 | 4 |
| EL 392 | Advanced IoT & Edge Computing | 3 | 0 | 2 | 4 |
| NU 302 | R & D Project | 1 | 0 | 6 | 4 |
| EC 441 | Power Electronics and Instrumentation | 3 | 0 | 2 | 4 |
| Total Semester L-T-P-C | 16 | 0 | 16 | 24 |
| Course Code | Course Title | L | T | P | C |
|---|---|---|---|---|---|
| Open Elective – I | 3 | 0 | 2 | 4 | |
| Open Elective – II | 3 | 0 | 2 | 4 | |
| Open Elective – III | 3 | 0 | 2 | 4 | |
| EC 461 | Capstone Project – I | 1 | 0 | 6 | 4 |
| EL 451 | Autonomous Systems | 3 | 0 | 2 | 4 |
| HSSM-IV | 3 | 0 | 0 | 3 | |
| Total Semester L-T-P-C | 16 | 0 | 14 | 23 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| NU 402 | Industry Practice/Project | 0 | 0 | 40 | 20 |
B Tech Robotics and Automation – Course Architecture – 1 Year IP/RP (Industry Practice/Research Practice)
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| MAT 112 | Calculus | 3 | 1 | 0 | 4 |
| EL 111 | Fundamentals of Electronics | 3 | 0 | 2 | 4 |
| Science I | 3 | 0 | 3 | 4 | |
| TA 111 | Fundamentals of Computer Programming | 2 | 0 | 4 | 4 |
| TA 202 | Engineering Graphics/ Workshop Practice | 2 | 0 | 2 | 3 |
| TA 212 | 1 | 0 | 4 | 3 | |
| TA 102 | Communication Skills/HSSM-I | 2 | 0 | 2 | 3 |
| 3 | 0 | 0 | 3 | ||
| NU 111 | Community Connect | 0 | 0 | 2 | 1 |
| Total semester L-T-P-C | 15 | 1 | 10 | 22 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| MAT 101 | Algebra & Differential Equation | 3 | 1 | 0 | 4 |
| Science II | 3 | 0 | 3 | 4 | |
| EL 101 | Digital Logic and Circuit | 3 | 0 | 2 | 3 |
| CS 102 | Data Structures | 3 | 0 | 2 | 4 |
| TA 202 | Engineering Graphics / Workshop Practice | 2 | 0 | 2 | 3 |
| TA 212 | 1 | 0 | 4 | 3 | |
| TA 102 | Communication Skills / HSSM-I | 2 | 0 | 2 | 3 |
| 3 | 0 | 0 | 3 | ||
| NU 112 | Community Connect | 0 | 0 | 2 | 1 |
| Total semester L-T-P-C | 16 | 1 | 10 | 22 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| MAT 221 | Probability & Random Process | 3 | 1 | 0 | 4 |
| EL 202 | Microprocessor & Microcontroller | 3 | 0 | 2 | 4 |
| ME 201 | Basic Mechanical Engineering | 3 | 1 | 0 | 4 |
| CS 2111 | Programming for Robotics | 2 | 0 | 4 | 4 |
| EL 211 | Signals & Systems | 3 | 1 | 0 | 4 |
| EL 332 | IOT and Sensor Networks | 3 | 0 | 2 | 4 |
| Total semester L-T-P-C | 17 | 3 | 8 | 24 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| ME 202 | Mechatronics Systems Design | 3 | 0 | 2 | 4 |
| EL 302 | Digital Image Processing | 3 | 0 | 2 | 4 |
| EL 312 | Advanced Embedded Systems | 3 | 0 | 2 | 4 |
| CS 4101 | Introduction to Linear and Nonlinear Optimization | 3 | 0 | 2 | 4 |
| EC 302 | Control Theory | 3 | 0 | 2 | 4 |
| HSSM-II | 3 | 0 | 0 | 3 | |
| Total semester L-T-P-C | 18 | 0 | 10 | 23 |
| Course Code | Course Title | L | T | P | C |
|---|---|---|---|---|---|
| CS 4111 | Computer Vision | 3 | 0 | 2 | 4 |
| CS 322 | Artificial Intelligence | 3 | 0 | 2 | 4 |
| CS 4131 | Machine Learning | 3 | 0 | 2 | 4 |
| EL 362 | Kinematics of the Robotics | 3 | 0 | 2 | 4 |
| CS 3101 | Database Systems & Cloud Integration | 3 | 0 | 2 | 4 |
| HSSM-III | 3 | 0 | 0 | 3 | |
| Total Semester L-T-P-C | 18 | 0 | 10 | 23 |
| Course Code | Course Title | L | T | P | C |
|---|---|---|---|---|---|
| EL 382 | Robotics Systems Integration | 3 | 0 | 2 | 4 |
| EL 322 | Industrial Control Robotics and Automation | 3 | 0 | 2 | 4 |
| CS 4341 | Deep Learning and Generative AI | 3 | 0 | 2 | 4 |
| EL 392 | Advanced IoT & Edge Computing | 3 | 0 | 2 | 4 |
| NU 302 | R & D Project | 1 | 0 | 6 | 4 |
| EC 441 | Power Electronics and Instrumentation | 3 | 0 | 2 | 4 |
| Total Semester L-T-P-C | 16 | 0 | 16 | 24 |
| Course Code | Course Title | L | T | P | C |
|---|---|---|---|---|---|
| Open Elective – I | 3 | 0 | 2 | 4 | |
| Open Elective – II | 3 | 0 | 2 | 4 | |
| NU 421 | Industry Practice-I/Research Practice-I | 0 | 0 | 24 | 12 |
| Total Semester L-T-P-C | 6 | 0 | 4 | 20 |
| Course code | Course | L | T | P | C |
|---|---|---|---|---|---|
| NU 402 | Industry Practice-II/Research Practice-II | 0 | 0 | 40 | 20 |
FAQs
Why is Robotics & Automation becoming such an important field?
Robotics & Automation is transforming industries worldwide through intelligent machines, autonomous systems, AI-driven manufacturing, smart logistics, healthcare robotics, drones, and Industry 4.0 technologies. As industries move toward digital transformation, the demand for engineers who can design, integrate, and manage intelligent automated systems is growing rapidly.
What makes Robotics & Automation different from traditional engineering branches?
Robotics & Automation is a highly interdisciplinary domain that combines:
- Electronics & Communication
- Computer Science & AI
- Mechanical Systems
- Control Engineering
- Embedded Systems
- IoT & Sensor Technologies
Students learn how hardware, software, AI, and intelligent control systems work together to create autonomous systems.
What kind of job roles can students get after this programme?
Graduates can explore diverse career opportunities such as:
- Robotics Engineer
- Automation Engineer
- Embedded Systems Engineer
- AI & Autonomous Systems Engineer
- Industrial Automation Specialist
- Control Systems Engineer
- Computer Vision Engineer
- IoT Engineer
- Drone Systems Engineer
- Mechatronics Engineer
- Robotics Software Developer
- R&D Engineer
Students may also pursue higher studies and research in Robotics, AI, Autonomous Systems, or Industry 4.0 domains.
Which industries hire Robotics & Automation engineers?
Robotics & Automation professionals are in demand across multiple sectors including:
- Manufacturing & Smart Factories
- Automotive & Electric Vehicles
- Warehousing & Logistics
- Healthcare & Medical Devices
- Aerospace & Defence
- Agriculture Automation
- Smart Infrastructure & Smart Cities
- Consumer Robotics
- Semiconductor & Electronics Industries
What are the key differentiators of the programme at NIIT University?
The programme is designed around NU’s core principles of:
- Industry-linked education
- Technology-based learning
- Research-driven pedagogy
- Seamless interdisciplinary education
Key differentiators include:
- Industry collaborations with companies
- Industry 4.0-ready laboratories
- Strong integration of AI, Embedded Systems, IoT, Computer Vision, and Robotics
- Project-based experiential learning
- Flexible Industry Practice / Research Practice model
- Strong focus on emerging technologies and intelligent systems
How is the programme aligned with Industry 4.0?
The curriculum includes:
- Industrial Robotics
- AI & Machine Learning
- Deep Learning & Generative AI
- IoT & Edge Computing
- Computer Vision
- Autonomous Systems
- Robotics Operating System (ROS)
- Smart Sensors & Automation
Students work on modern automation and intelligent system technologies widely used in Industry 4.0 environments.
Will students get hands-on practical exposure?
Yes. The programme strongly emphasizes experiential learning through:
- Robotics and embedded system labs
- Mini-projects and capstone projects
- Prototype development
- Industry projects
- Research-oriented projects
- Industry Practice and internships
Students gain exposure to real-world engineering problems from early semesters.
What is unique about NU’s Industry Practice model?
NIIT University offers flexible curricular architecture where students can choose:
- 6-month Industry Practice
- 1-Year Industry Practice
- 1-Year Research Practice
Students work closely with industry or research organizations under joint supervision of faculty and industry mentors. This model significantly improves practical exposure and employability.
Is Robotics & Automation only about coding or only about mechanical systems?
No. Robotics & Automation is a balanced combination of:
- Hardware
- Software
- Electronics
- AI
- Sensors
- Control Systems
- Intelligent Decision Making
Students develop both programming and hardware integration skills.
What kind of laboratories and infrastructure are available?
NU is developing Industry 4.0-ready laboratories equipped for:
- Robotics & Automation
- Embedded Systems
- IoT & Sensor Networks
- AI & Computer Vision
- Industrial Automation
- Control Systems
- Rapid Prototyping and Product Development
The focus is on application-oriented and hands-on learning.
Can students pursue higher studies or research after this programme?
Absolutely. The interdisciplinary nature of the programme prepares students for:
- MS/MTech in Robotics, AI, Automation, Mechatronics, Embedded Systems, etc.
- Research careers in intelligent systems and autonomous technologies
- Startup and innovation ecosystems
- PhD and advanced R&D opportunities
Is Robotics & Automation a future-proof career option?
Yes. Robotics, AI, autonomous systems, and intelligent automation are expected to play a major role in future industries. Governments and industries worldwide are investing heavily in:
- Smart manufacturing
- AI-driven systems
- Autonomous mobility
- Defence technologies
- Healthcare robotics
- Smart infrastructure
This creates long-term career opportunities for skilled Robotics & Automation engineers.
