B.Tech Electronics and Communication Engineering (Artificial Intelligence and Machine Learning)
Programme Overview
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.
Major Tracks
- Edge Intelligence
- AI in Healthcare
- AI Computing Platform
- Deep Learning Architectures
- Augmented and Virtual Reality
Duration & Fees
Duration
4 Years
Applications Open for 2026
Fee Per Year
₹ 3,65,000
Scholarship
| Scholarship for AY 2025-26 | JEE Percentile | MH-CET Percentile |
|---|---|---|
|
Dr. Vishwanath Karad Scholarship |
94 & Above |
95 & Above |
|
MIT-WPU Scholarship I |
92 & Above |
93 & Above |
|
MIT-WPU Scholarship II |
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
Eligibility
The candidates should have appeared in JEE 2025 / MHT-CET 2025 / PERA 2025 / MHT-CET-B* 2025 / NEET* 2025. [*Applicable only for 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 Bioengineering] (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.
Selection Process
The selection process 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 Bioengineering programme].
Programme Highlights
- 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.
Programme Structure
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
I |
UC | Indian Constitution | 1 |
|
I |
UC | Environment and Sustainability | 1 |
|
I |
UC | Yoga - I | 1 |
|
I |
UC | Social Leadership Development Program | 1 |
|
I |
UC | Financial Literacy | 1 |
|
I |
PF | Linear Algebra and Differential Calculus | 3 |
|
I |
PF | Engineering Physics | 3 |
|
I |
PF | Basics of Electrical Engineering | 4 |
|
I |
PF | Engineering Mechanics | 3 |
|
I |
PF | Programming and Problem Solving | 3 |
|
I |
PF | Python Programming | 1 |
| Total Credits: | 22 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
II |
UC | Yoga - II | 1 |
|
II |
UC | Co-creation | 1 |
|
II |
UC | AI for everyone | 2 |
|
II |
UC | Foundation of Peace | 2 |
|
II |
UC | Indian Knowledge System (General) | 2 |
|
II |
UC | Sports | 1 |
|
II |
PF | Integral Calculus | 3 |
|
II |
PF | Basics of Electronics Engineering | 3 |
|
II |
PF | Digital Electronics | 4 |
|
II |
PF | Engineering Chemistry | 3 |
| Total Credits: | 22 |
| Semester | Course Type | Course Name/ Course Title | Total Credits |
|---|---|---|---|
|
III |
UC | Spiritual and Cultural heritage: Indian Experience |
2 |
|
III |
UC | Research Innovation Design Entrepreneurship (RIDE) |
1 |
|
III |
UE | University Electives - I | 3 |
|
III |
PF | Calculus and Statistical Methods | 4 |
|
III |
PM | Signals and Systems | 3 |
|
III |
PF | Electronics Devices and Circuits | 4 |
|
III |
PF | Data Structures and Algorithms | 3 |
|
III |
Program Capstone Project/ Seminar and Internships |
Sensors and Actuators | 1 |
| III | Program Capstone Project/ Seminar and Internships |
Data Science | 1 |
| Total Credits: | 22 |
| Semester | Course Type | Course Name/ Course Title | Total Credits | |
|---|---|---|---|---|
|
IV |
UC | Rural Immersion | 1 | |
|
IV |
UC | Life Transformation Skills | 1 | |
|
IV |
UE | University Electives - II | 3 | |
|
IV |
PM | Analog Circuits and Applications | 3 | |
|
IV |
PM | Analog and Digital Communication | 4 | |
|
IV |
PM | Control Systems and Fuzzy Logic | 3 | |
|
IV |
PM | Microcontroller and Applications | 4 | |
|
IV |
PM | Optimization Techniques | 2 | |
|
IV |
Program Capstone Project/ Seminar and Internships |
Object Oriented Programming | 1 | |
| Total Credits: | 22 | |||
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
V |
UC | Managing Conflicts Peacefully: Tools and Techniques |
2 |
|
V |
UE | University Electives - III | 3 |
|
V |
PE | Program Elective - I | 4 |
|
V |
PM | Digital Signal Processing | 4 |
|
V |
PM | Artificial Intelligence | 2 |
|
V |
PM | Machine Learning | 4 |
|
V |
PM | IOT Architectures and Protocols | 3 |
| Total Credits: | 22 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
VI |
UC | National Academic Immersion Program | 2 |
|
VI |
PE | Program Elective - II | 4 |
|
VI |
PM | Machine Vision | 4 |
|
VI |
PM | Deep Neural Networks | 4 |
|
VI |
PM | Computer Networks and Security | 4 |
|
VI |
PM | VLSI Design | 4 |
| Total Credits: | 22 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
VII |
PE | Program Elective - III | 4 |
|
VII |
Program Capstone Project/Seminar and Internships | Internship | 12 |
| Total Credits: | 16 |
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
VIII |
PE | Program Elective - IV | 4 |
|
VIII |
Program Capstone Project/ Seminar and Internships |
Capstone Project | 13 |
| Total Credits: | 17 |
Career Prospects
Machine Learning Engineer
AI Research Scientist
Data Scientist
Natural Language Processing Engineer
Computer Vision Engineer
AI/ML Consultant
Deep Learning Engineer
Embedded Systems Engineer
Avionics Engineer
Research and Development Engineer
Programme Outcomes
- 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.
Placements & Recruiters
100% Placement Assistance
Top Recruiters
FAQs
MIT-WPU's B.Tech Electronics and Communication Engineering (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 Electronics and Communication Engineering (AI & ML) programme have numerous career opportunities in the field of electronics and communication engineering. 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.
The B.Tech Electronics and Communication Engineering (AI & ML) programme at MIT-WPU offers several specialised tracks to help students develop expertise in emerging areas. Key specialisations include:
- Edge Intelligence
- AI in Healthcare
- AI Computing Platforms
- Deep Learning Architectures
- Augmented and Virtual Reality
These specialisations are supported by electives and certifications in advanced technologies such as computer vision, AI robotics, and natural language processing. The curriculum is designed to provide niche skills and prepare students to excel in their chosen domain within AI and machine learning, ensuring readiness for industry demands and future technological advancements.
The B.Tech Electronics and Communication Engineering (AI & ML) programme at MIT-WPU emphasises responsible AI development, covering ethics, algorithmic bias, transparency, and accountability. Students learn to understand AI's societal impact and design fair, trustworthy systems. This prepares graduates to create ethical AI solutions that prioritise equity, privacy, and social responsibility in their professional work.
The MIT-WPU B.Tech Electronics and Communication Engineering (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 curriculum, 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
