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M-TECH in Robotics And Automation at Symbiosis International University
Pune, Maharashtra
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About the Specialization
What is Robotics and Automation at Symbiosis International University Pune?
This Robotics and Automation program at Symbiosis International University focuses on advanced concepts in robotic systems, industrial automation, and intelligent control. It addresses the growing need for skilled professionals in India''''s rapidly expanding manufacturing, healthcare, and logistics sectors, emphasizing practical application and interdisciplinary knowledge for modern industrial challenges.
Who Should Apply?
This program is ideal for engineering graduates in mechanical, electronics, computer science, or related fields seeking to specialize in cutting-edge automation technologies. It also caters to working professionals aiming to upgrade their skills in areas like AI, IoT, and advanced robotics to meet evolving industry demands in India.
Why Choose This Course?
Graduates of this program can expect promising career paths as Robotics Engineers, Automation Specialists, AI/ML Engineers, or Mechatronics System Designers in leading Indian and multinational companies. Entry-level salaries typically range from INR 6-10 LPA, with significant growth potential as experience increases, contributing to India''''s push for ''''Make in India'''' and Industry 4.0 initiatives.
Student Success Practices
Foundation Stage
Master Core Mathematical & Control Fundamentals- (Semester 1-2)
Dedicate significant effort to building a strong foundation in Advanced Engineering Mathematics and Industrial Automation & Control. Utilize online platforms like NPTEL for supplementary lectures and practice problems. Form study groups to discuss complex topics and solve problems collaboratively.
Tools & Resources
NPTEL courses on Control Systems and Advanced Mathematics, MATLAB/Simulink for simulations, Standard textbooks and reference materials
Career Connection
A solid grasp of these fundamentals is crucial for designing and analyzing robotic systems, which is a key requirement for R&D and design roles in automation companies.
Hands-on Lab & Mini Project Engagement- (Semester 1-2)
Actively participate in all lab sessions (e.g., Industrial Automation & Control Lab, Advanced Sensors & Actuators Lab) and commit fully to the Mini Project. Focus on understanding the practical implementation of theoretical concepts, troubleshooting, and documenting your work meticulously. Seek feedback from professors and lab assistants.
Tools & Resources
Lab equipment and software (PLCs, microcontrollers, sensor kits), GitHub for project version control, Project management tools (Trello, Asana)
Career Connection
Practical experience gained in labs and projects is invaluable for gaining internships and entry-level positions requiring hands-on skills in robotics and automation.
Develop Foundational Programming Skills- (Semester 1-2)
Beyond academic requirements, continuously enhance programming skills relevant to robotics (e.g., Python for AI/ML, C++ for real-time systems, ROS). Participate in coding challenges on platforms like HackerRank or LeetCode. This will be critical for later semesters and project work.
Tools & Resources
Python, C++ programming languages, Robot Operating System (ROS) basics, Online coding platforms (HackerRank, LeetCode)
Career Connection
Strong programming skills are non-negotiable for almost all roles in robotics and automation, especially in AI, machine vision, and robot control, improving employability significantly.
Intermediate Stage
Focus on Elective Specialization and Applied AI/ML- (Semester 2-3)
Choose electives strategically (e.g., Mechatronics System Design, Embedded Systems, HRI) that align with your career aspirations. Dive deep into Artificial Intelligence, Machine Learning, Deep Learning for Robotics, and Machine Vision, applying concepts through mini-projects and competition participation.
Tools & Resources
TensorFlow/PyTorch, OpenCV for image processing, Robotics simulation environments (Gazebo, V-REP), Kaggle for data science competitions
Career Connection
Specialized knowledge in chosen electives and advanced AI/ML skills are highly sought after for specific roles in robot design, intelligent automation, and autonomous systems.
Engage in Industry-Relevant Project Phase - I- (Semester 2)
Treat Project Phase - I as an opportunity to solve a real-world problem. Collaborate with faculty, industry mentors (if possible), and peers. Develop a robust problem statement, implement solutions, and document progress. Look for opportunities to publish initial findings in conferences or journals.
Tools & Resources
Project management software, Academic databases (IEEE Xplore, Scopus), Professional networking platforms (LinkedIn)
Career Connection
A well-executed project demonstrates problem-solving abilities, technical skills, and research aptitude, which are key during internship and job interviews for R&D roles.
Build a Professional Network and Seek Internships- (Semester 3)
Actively network with alumni, industry professionals, and faculty. Attend webinars, workshops, and industry expos. Start applying for internships early in Semester 3 to gain practical exposure in companies working on industrial automation, IoT, or robotics in India.
Tools & Resources
LinkedIn for networking, Internshala, Naukri.com for internship searches, University career services
Career Connection
Internships provide invaluable industry experience, often leading to pre-placement offers, and help build connections essential for future career growth and job placements.
Advanced Stage
Excel in Project Phase - II for Industry Readiness- (Semester 4)
Dedicate maximum effort to Project Phase - II, aiming for an innovative and impactful solution. Focus on completing a deployable prototype or a comprehensive research paper. Document every aspect meticulously, from design to testing and evaluation. Prepare for rigorous defense presentations.
Tools & Resources
Advanced simulation tools, Prototyping facilities, Scientific writing tools (LaTeX, Grammarly)
Career Connection
A strong final project is your biggest asset for placements, showcasing advanced problem-solving, innovation, and implementation skills to potential employers in the robotics and automation industry.
Strategic Placement Preparation and Skill Refinement- (Semester 3-4)
Begin placement preparation early by refining your resume, practicing interview skills (technical and HR), and working on aptitude tests. Identify target companies and roles. Focus on mastering concepts from core robotics, AI/ML, and your chosen specialization. Participate in mock interviews.
Tools & Resources
Online aptitude test platforms, Interview preparation guides (GeeksforGeeks, InterviewBit), Resume building workshops
Career Connection
Proactive and targeted preparation ensures you are well-equipped to secure top placements in leading robotics and automation companies, maximizing your career launch opportunities.
Explore Entrepreneurship or Higher Studies- (Semester 4)
For those inclined, explore entrepreneurship opportunities by identifying market gaps in the Indian robotics sector and developing business models. Alternatively, prepare for competitive exams (GATE, GRE) or research proposals if considering PhD or further advanced studies in India or abroad.
Tools & Resources
Startup incubators/accelerators, Mentorship from industry leaders, GATE/GRE study materials, Research journals and conferences
Career Connection
Whether building a startup or pursuing a PhD, these avenues offer diverse paths for advanced impact and leadership within the rapidly evolving robotics and automation landscape.
Program Structure and Curriculum
Eligibility:
- Bachelor''''s degree in Engineering/Technology in Mechanical / Production / Mechatronics / Electronics / Electronics & Telecommunication / Instrumentation / Computer Science / Information Technology / Chemical / Biomedical / Biotechnology / Aeronautical / Automobile Engineering or equivalent with a minimum of 50% marks (45% for SC/ST) or equivalent grade. Candidates appearing for final year examinations can also apply, but their admission will be subject to obtaining a minimum of 50% marks (45% for SC/ST) or equivalent grade, at the qualifying examination.
Duration: 2 years (4 semesters)
Credits: 74 Credits
Assessment: Assessment pattern not specified
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTAR 101 | Advanced Engineering Mathematics | Core | 4 | |
| MTAR 102 | Industrial Automation and Control | Core | 4 | |
| MTAR 103 | Advanced Sensors and Actuators | Core | 4 | |
| MTAR 104 | Research Methodology | Core | 3 | |
| MTAR 105 | Industrial Automation and Control Lab | Lab | 1 | |
| MTAR 106 | Advanced Sensors and Actuators Lab | Lab | 1 | |
| MTAR 107 | Seminar | Seminar | 2 | |
| MTAR 108 | Mini Project | Mini Project | 3 |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTAR 201 | Robot Dynamics and Control | Core | 4 | |
| MTAR 202 | Machine Vision and Image Processing | Core | 4 | |
| MTAR 203 | Artificial Intelligence and Machine Learning | Core | 4 | |
| MTAR 204A | Mechatronics System Design (Elective I) | Elective | 3 | |
| MTAR 204B | Embedded System Design (Elective I) | Elective | 3 | |
| MTAR 204C | Digital Signal Processing (Elective I) | Elective | 3 | |
| MTAR 204D | Advanced Drives and Motion Control (Elective I) | Elective | 3 | |
| MTAR 205 | Robot Dynamics and Control Lab | Lab | 1 | |
| MTAR 206 | Machine Vision and Image Processing Lab | Lab | 1 | |
| MTAR 207 | Elective I Lab | Elective Lab | 1 | |
| MTAR 208 | Project Phase - I | Project | 4 |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTAR 301 | Deep Learning for Robotics | Core | 4 | |
| MTAR 302 | Industrial Internet of Things (IIoT) | Core | 4 | |
| MTAR 303A | Human Robot Interaction (Elective II) | Elective | 3 | |
| MTAR 303B | Advanced Manufacturing Systems (Elective II) | Elective | 3 | |
| MTAR 303C | Autonomous Mobile Robots (Elective II) | Elective | 3 | |
| MTAR 303D | Optimization Techniques (Elective II) | Elective | 3 | |
| MTAR 304 | Deep Learning for Robotics Lab | Lab | 1 | |
| MTAR 305 | Industrial Internet of Things Lab | Lab | 1 | |
| MTAR 306 | Elective II Lab | Elective Lab | 1 | |
| MTAR 307 | Internship | Internship | 3 |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MTAR 401 | Project Phase - II | Project | 12 |
