B.Tech Electronics and Communication Engineering (Artificial Intelligence and Machine Learning)
The B.Tech in Electronics and Communication Engineering with a specialisation in AI & ML at MIT-WPU is tailored to combine electronics and communication fundamentals with advanced AI and ML concepts. This programme integrates traditional topics such as signal processing, semiconductor devices, and communication systems with modern subjects like neural networks, deep learning, computer vision, and natural language processing.
The curriculum equips you with the expertise to develop innovative AI applications integrated with communication technologies and design advanced algorithms to tackle industry challenges. Through hands-on practical labs, workshops, and internships, you'll gain exposure to cutting-edge developments in electronics and AI/ML, preparing you for this rapidly growing field.
- Edge Intelligence
- AI in Healthcare
- AI Computing Platform
- Deep Learning Architectures
- Augmented and Virtual Reality
Last Date to Apply : 26 May 2025
B.Tech Electronics and Communication Engineering (Artificial Intelligence and Machine Learning)
| Scholarship for AY 2025-26 | JEE Percentile | MH-CET Percentile |
| Dr. Vishwanath Karad Scholarship (100%) | 94 & Above | 95 & Above |
| MIT-WPU Scholarship I (50%) | 92 & Above | 93 & Above |
| MIT-WPU Scholarship II (25%) | 91 & Above | 92 & Above |
Note: Best of JEE or MHT-CET Score will be considered for availing the scholarship.
*Terms & Conditions apply:
- All Scholarships are awarded on a First Come First Serve basis. All Scholarships are awarded as fee adjustments.
- To continue the scholarship for the entire duration of the programme, a minimum level of the academic score has to be maintained at an 8 CGPA across all semesters, attendance is to be maintained at a minimum of 80 percent, with no live backlogs in any subject/programme and no semester break, and there should be no disciplinary action against the student.
For more detailed information visit our website: https://mitwpu.edu.in/scholarships
The candidates should have appeared in JEE 2025 / MHT-CET 2025 / PERA 2025 / MHT-CET-B* 2025 / NEET* 2025. [*Applicable only for B.Tech Bioengineering programme] conducted by the Competent Authority
AND
Minimum 50% aggregate in PCM or PCB* or Physics & Mathematics with any Technical Vocational Subject. Physics, Mathematics/Biology* & English are Compulsory subjects with Chemistry/Biotechnology* or Technical Vocational Courses in 10+2/Class 12th or equivalent examination [*Applicable only for B.Tech Bioengineering programme] (at least 45% marks, in case of Reserved category candidate belonging to Maharashtra State only).
OR
Minimum 60% marks in Diploma in Engineering & Technology in an appropriate branch from Government approved technical board.
The selection process for B.Tech programmes is based on JEE 2025/ MHT-CET 2025/ PERA 2025/ MHT-CET-B* 2025/ NEET* 2025 score and a Statement of Purpose (500 words) written by the candidate. [*Applicable only for B.Tech Bioengineering programme].
- Advanced Labs : Gain hands-on experience with DELL PowerEdge Servers and AIoT SerBot Prime X Robot, utilising NVIDIA RTX A6000 GPUs to deeply explore AI/ML applications.
- Learn Emerging Technologies for Future Readiness : Focus on AI, IoT, and robotics to develop expertise in autonomous systems, robotic design, and AI computing.
- Collaboration with Industry : Benefit from internships and partnerships with companies like Bosch, Accenture, and Volkswagen for real-world exposure and career readiness.
- A Well-Rounded Approach : Develop technical expertise alongside personal growth, ethics, and understanding of societal impacts to become an industry-ready AI professional.
- International Immersions : Participate in national and international immersion programmes to broaden your global perspective and prepare for international industry demands.
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
I |
University Core |
Effective Communication |
1 |
|
I |
University Core |
Critical Thinking |
1 |
|
I |
University Core |
Environment and Sustainability |
1 |
|
I |
University Core |
Foundations of Peace |
2 |
|
I |
University Core |
Yoga - I |
1 |
|
I |
University Core |
SLDP |
1 |
|
I |
Programme Foundation |
Linear Algebra and Differential Calculus |
3 |
|
I |
Programme Foundation |
Chemistry |
3 |
|
I |
Programme Foundation |
Ideas and Innovations in Manufacturing |
1 |
|
I |
Programme Foundation |
Physics |
3 |
|
I |
Programme Foundation |
Engineering Graphics |
3 |
|
I |
Programme Major |
Multisim Lab |
1 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
II |
University Core |
Advanced Excel |
1 |
|
II |
University Core |
Financial Literacy |
1 |
|
II |
University Core |
Yoga - II |
1 |
|
II |
University Core |
Co-creation |
1 |
|
II |
University Core |
Indian Constitution |
1 |
|
II |
University Core |
IKS(General) |
2 |
|
II |
University Core |
Sports |
1 |
|
II |
Programme Foundation |
Engineering Mechanics |
3 |
|
II |
Programme Foundation |
Programming and Problem Solving |
3 |
|
II |
Programme Foundation |
Integral Calculus |
3 |
|
II |
Programme Foundation |
Biology For Engineers |
2 |
|
II |
Programme Major |
Basics of Electrical and Electronics Engineering |
3 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
III |
University Core |
Research Innovation Design Entrepreneurship (RIDE) |
1 |
|
III |
University Core |
Spiritual & Cultural Heritage; Indian Experience |
2 |
|
III |
University Electives |
UE - I |
3 |
|
III |
University Electives |
UE-II |
3 |
|
III |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Project Based Learning - I (Sensors and Actuators Lab) |
1 |
|
III |
Programme Foundation |
Probability and Statistics |
4 |
|
III |
Programme Foundation |
Signals and Systems |
4 |
|
III |
Programme Major |
Digital Electronics |
4 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
IV |
University Electives |
UE-III |
3 |
|
IV |
University Core |
Rural Immersion |
1 |
|
IV |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Project Based Learning - II (Data Science Lab) |
1 |
|
IV |
University Core |
Life Transformation Skills |
1 |
|
IV |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Data Structures and Algorithms |
2 |
|
IV |
Programme Major |
Communication Systems |
4 |
|
IV |
Programme Major |
Analog Circuits and Applications |
4 |
|
IV |
Programme Major |
Control System and Fuzzy Logic |
3 |
|
IV |
Programme Major |
Microcontroller and Applications |
4 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
V |
University Core |
Managing Conflicts Peacefully: Tools and Techniques |
2 |
|
V |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Project Based Learning - III (OOP Lab) |
1 |
|
V |
Programme Electives |
Programme Elective - I |
4 |
|
V |
Programme Foundation |
IKS-2 |
2 |
|
V |
Programme Major |
Computer Network and Security |
4 |
|
V |
Programme Major |
Artificial Intelligence and Machine Learning |
4 |
|
V |
Programme Major |
Database Management System |
1 |
|
V |
Programme Major |
Image Processing and Pattern Recognition |
4 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
VI |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Project Based Learning - IV (Mini Project) |
1 |
|
VI |
University Core |
National Academic Immersion |
2 |
|
VI |
Programme Electives |
Programme Elective - II |
4 |
|
VI |
Programme Major |
Deep Neural Network |
4 |
|
VI |
Programme Major |
Natural Language Processing |
4 |
|
VI |
Programme Major |
Optimization Techniques |
4 |
|
VI |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Seminar |
1 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
VII |
Programme Electives |
Programme Elective - III |
4 |
|
VII |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Internship |
12 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
VIII |
Programme Electives |
Programme Elective -IV |
4 |
|
VIII |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Capstone Project |
13 |
- Apply engineering principles and AI/ML algorithms to solve challenges in electronic systems, communication processes, and AI-driven applications.
- Design and implement AI-based systems and electronic applications to address global issues in healthcare, transportation, and communication.
- Conduct innovative research in AI, deep learning, and robotics to develop advanced technologies that positively impact society.
- Create solutions that are ethical and mindful of social, environmental, and cultural considerations.
- Gain expertise in AI, ML, embedded systems, and signal processing to build a career in telecommunications, healthcare, automotive, and data science industries.
100% placement assistance
MIT-WPU's B.Tech in AI & ML integrates electronics and communication systems with artificial intelligence and machine learning concepts. Core subjects include semiconductor devices, analogue and digital circuits, and signal processing. Advanced topics cover machine learning algorithms, neural networks, deep learning, computer vision, and natural language processing. The programme also includes hands-on learning through projects and the development of AI-driven interactive systems, combining theoretical knowledge with practical applications to build real-world AI solutions.
The programme offers industry-based projects and internships to provide practical experience in AI and electronics domains. Students work on embedded systems, AI computing platforms, and robotics while solving real-world problems with leading companies like Bosch, Accenture, and Volkswagen. With 100% internship assistance, you gain opportunities to apply your learning to live projects, enhancing your skills and employability.
Graduates of the B.Tech in AI & ML programme have numerous career opportunities in the electronics and communication engineering sectors. You can pursue roles such as Machine Learning Engineer, Data Scientist, AI Research Scientist, AI Consultant, or Deep Learning Engineer. Industries like telecommunications, automotive, healthcare, biotechnology, finance, and AI startups are constantly seeking AI-based solutions, making this field highly desirable with a growing demand for skilled professionals.
Yes, the programme offers specialised tracks in areas such as AI in Healthcare, Edge Intelligence, Deep Learning Architectures, and AI Computing Platforms. It includes electives and certifications tailored to your career aspirations, covering advanced technologies like computer vision, AI robotics, and natural language processing. These specialisations provide niche skills and prepare you to excel in your chosen area of AI and machine learning.
At MIT-WPU, a significant focus of the programme is the ethical development of AI. You will explore the societal implications of AI and learn to responsibly and equitably design AI-based applications. The curriculum includes topics such as AI ethics, algorithmic bias, trustworthiness, explainability, and accountability of AI systems. This ensures you understand the broader social contexts of your work and make informed decisions as engineers or technical professionals, taking ownership of the impact of your creations.
The MIT-WPU B.Tech AI & ML programme keeps you ahead of the curve by offering exposure to cutting-edge technologies, state-of-the-art labs, and real-world industry projects in collaboration with leading companies. With hands-on, project-based learning and research-driven courses, you are equipped with the skills to adapt to emerging trends and make meaningful advancements in the fast-paced world of AI and ML.
MIT-WPU offers a modern curriculum that combines experiential learning with strong industry collaborations. You gain hands-on experience with real-world projects and develop in-demand AI and ML skills, preparing you for a rewarding career in the rapidly growing tech sector.
admissions@mitwpu.edu.in 
