The curriculum for B. Tech. Electronics and Communication Engineering is equipped with a National Educational Policy. The focus of the program lies on core concepts of electronics, artificial intelligence, and Machine learning empowering our students to develop unique expertise they can offer to the industry to climb the path of bright careers and reach professional highs. Inspired by Indian values, the curriculum nurtures students with invaluable qualities such as impeccable ethics, pursuit of new knowledge, and research attitude. All-in-all, technical training by esteemed teachers, personality grooming, and inspiration to innovation leads them to unleash their true potential professionally and personally making them evolved citizens of this new world!
For Maharashtra State Candidature Candidate and All India Candidature Candidate. -
The candidate, -
(i) should have passed minimum three years or two years (Lateral Entry) Diploma Course in Engineering and Technology with at least 45% marks (at least 40% marks in case of Candidates of Reserved categories, Economically Weaker Section and Persons with Disability category belonging to Maharashtra State) in any branch of Engineering and Technology from an All-India Council for Technical Education (AICTE) or Central Government or State Government approved Institution or its equivalent;
or
(ii) should have passed B.Sc. Degree from a University Grants Commission (UGC) or Association of Indian Universities recognized University with at least 45% marks (at least 40% marks in case of candidates of Reserved categories, Economically Weaker Section and Persons with Disability category belonging to Maharashtra State) and passed HSC or its equivalent examination with Mathematics as a subject;
or
(iii) should have passed three years D. Voc. Stream in the same or allied sector; and
(iv) Any other eligibility criteria and requirement declared from time to time by the appropriate authority as defined under the Act.
The selection process for the programmes is based on Diploma aggregate scores (Provisional Admissions are offered based on5th semester scores, in case results of final semester are awaited)
| Sr No | Semester 1 |
|---|---|
| 1 | Probability and Statistics |
| 2 | Engineering Biology |
| 3 | Fundamentals of Computer Science |
| 4 | Basic Electrical Engineering |
| 5 | Manufacturing Practices |
| 6 | Design Thinking |
| 7 | Indian Knowledge System - I |
| 8 | Yoga and Meditation - I |
| Sr No | Semester 2 |
|---|---|
| 1 | Linear Algebra and Calculus |
| 2 | Engineering Physics |
| 3 | Basic Electronics Engineering |
| 4 | Engineering Drawing |
| 5 | Communication Skills |
| 6 | Yoga and Meditation - II |
| Sr No | Semester 3 |
|---|---|
| 1 | Electronics Devices and Circuits |
| 2 | Signals and Systems |
| 3 | Data Structure and Algorithm |
| 4 | Digital Electronics |
| 5 | Open Elective 1 |
| 6 | Finance and Costing |
| 7 | Field Project |
| 8 | Engineering Economics |
| 9 | Open Elective 2 |
| Sr No | Semester 4 |
|---|---|
| 1 | Integrated Circuits and Applications |
| 2 | Communication Systems |
| 3 | Control Systems |
| 4 | Sensor Technology |
| 5 | Python Programming |
| 6 | Engineering Project Management |
| 7 | Open Elective 3 |
| 8 | Employability and Entrepreneurship Development |
| 9 | Environmental Science for Engineers |
| Sr No | Semester 5 |
|---|---|
| 1 | Computer Networks & Security |
| 2 | Digital Signal Processing |
| 3 | AI Techniques |
| 4 | Microcontroller and Applications |
| 5 | Professional Elective - I |
| 6 | Open Elective 4 |
| Sr No | Semester 6 |
|---|---|
| 1 | Optimization Techniques |
| 2 | Machine Learning Techniques |
| 3 | Data Storytelling and Visualization |
| 4 | Intellectual Property Rights |
| 5 | Professional Elective - 2 |
| 6 | Professional Elective -3 |
| Sr No | Semester 7 |
|---|---|
| 1 | Deep Learning |
| 2 | Professional Elective - 4 |
| 3 | Research Methodology |
| 4 | Internship |
| Sr No | Semester 8 |
|---|---|
| 1 | Ex-AI |
| 2 | Professional Elective - 5 |
| 3 | Professional Elective - 5 |
| 4 | Elective IV(B) |
| 5 | IOT |
| 6 | Project |
Our students will be poised for exciting career opportunities in diverse industries. With expertise in AIML integrated into their ECE foundation.
AI / Software Engineer: Designing and implementing AI solutions for automation, predictive analytics, and decision-making systems. Embedded Systems Engineer: Developing intelligent systems for IoT devices, smart appliances, and connected infrastructure. Communication Systems Engineer: Designing advanced communication protocols and networks for efficient data transmission and connectivity.Robotics Engineer: Building autonomous systems and robotic platforms leveraging AI and machine learning algorithms. Research Scientist: Contributing to cutting-edge research in areas like computer vision, natural language processing, and deep learning.Embarking on a B.Tech in Electronics and Communication Engineering with a specialization in Artificial Intelligence and Machine Learning (AIML) opens a plethora of entrepreneurial avenues in the tech-driven world.
AI-Based Product Development: Startups on AI-powered products tailoring industry needs for forecasting and predictive analysis to meet the challenges in the industry. IoT-based Innovations: Devising smart devices for automation solutions. AI/ML/ Data Science Ventures: Leveraging the expertise to provide insights and predictive analytics in optimized decision-making. Consultancy Services and training: Developing AI-driven education and training platforms and consultancy projects for business decisions.Abundant opportunities lie for students with varied areas of higher education
Advanced Research and Masters degree: Students can get better prospects for master’s in recent fields of deep learning, Explainable AI, Computer Vision, Natural Language Processing, and Robotics, further leading them to Ph.D. in reputed institutions across the globe. Moreover, ample openings lie in the area of Communication Systems, Embedded systems, and AI-driven Electronics Systems.Interdisciplinary Fields: A grasp on the current trends of Artificial Intelligence and Machine Learning can enable students to work in interdisciplinary programs such as cognitive science, computational neuroscience, or bioinformatics, applying AI and machine learning techniques to diverse domains like healthcare, fintech, manufacturing and management offerings.
