B.Tech Electronics And Computer Engineering - AI and ML Applications
Program details
The B.Tech. program in Electronics & Computer Engineering (AI & ML Applications) offered by UPES School of Advanced Engineering is meticulously designed to align with the demands of the Industry 4.0 era. With Artificial Intelligence (AI) being a cornerstone of modern technological advancements such as big data analytics, robotics, and the Internet of Things (IoT), this specialization equips students with the skills and knowledge required to tackle intricate real-world engineering challenges.
This program delves deep into the realm of AI and Machine Learning (ML), imparting comprehensive insights into their applications across diverse sectors. Through a combination of theoretical instruction and practical hands-on experience, students will develop the competence to conceptualize, analyze, and resolve intricate engineering problems in real-time scenarios. The curriculum integrates foundational electronics and computer engineering principles with cutting-edge AI and ML techniques, ensuring graduates possess a holistic understanding of both domains.
Graduates of this program will emerge as adept professionals capable of spearheading innovative solutions within the Industry 4.0 landscape. By mastering AI and ML applications, they will be well-equipped to address the technological needs of next-generation industries, effectively bridging the gap between theory and practical implementation. The program's emphasis on modeling, analysis, and problem-solving will empower students to contribute meaningfully to the ongoing evolution of AI-driven technologies, establishing them as valuable assets in the contemporary engineering workforce.
Program Highlights
- Engage in a rigorous curriculum covering key areas such as statistics & data science, soft computing techniques, artificial intelligence, deep learning, and natural language processing.
- Gain practical experience through hands-on projects, allowing you to apply theoretical concepts to real-world AI and machine learning challenges.
- Learn from experienced faculty members who are experts in the field, providing you with industry-relevant insights and guidance.
- The B.Tech. in Electronics & Computer Engineering (AI & ML Applications) program explores the latest advancements in AI and ML technologies, preparing you to contribute to the rapidly evolving tech landscape.
- Benefit from an interdisciplinary learning environment, fostering collaboration between electronics and computer engineering in AI and ML applications.
- Access industry interactions, workshops, and internships, enhancing your skills and making you job-ready for roles in AI and machine learning domains.
Future Scope / Industry Trends
The B.Tech. in Electronics & Computer Engineering (AI & ML Applications) program by UPES School of Advanced Engineering offers a promising future scope. With industries across the board undergoing digital transformation, this specialization presents abundant job opportunities. Renowned companies like Microsoft, Intel, Qualcomm, IBM, Apple, Cognizant, and Bosch are deeply engaged in integrating AI and ML applications into their core operations. Graduates of this program are well-positioned to tap into these opportunities. Moreover, students can opt for advanced studies in data science and machine learning, further enhancing their expertise and career prospects in this rapidly evolving field.
Career Opportunities
Graduates of the B.Tech. in Electronics & Computer Engineering (AI & ML Applications) program from UPES School of Advanced Engineering are poised for a dynamic range of career opportunities at the intersection of cutting-edge technology. Equipped with a comprehensive understanding of electronics, computer engineering, artificial intelligence, and machine learning, they can thrive in various industries. Graduates may choose paths as AI and ML engineers, developing intelligent systems and algorithms, or as software engineers specializing in AI-driven applications. They could excel as data scientists, extracting insights from vast datasets to inform strategic decisions, or as research scientists, contributing to advancements in AI and ML. Opportunities abound in sectors like robotics, automation, healthcare, finance, and more. Graduates could also venture into entrepreneurship, leveraging their expertise to create innovative tech startups. With a solid foundation provided by UPES, these professionals are prepared to contribute meaningfully to the ever-evolving landscape of AI and ML, addressing complex challenges and shaping the future of technology.
Placements
The placements of the B.Tech. in Electronics & Computer Engineering (AI & ML Applications) program by UPES School of Advanced Engineering exemplify excellence and industry relevance. With a steadfast commitment to fostering skilled professionals, UPES ensures that graduates are well-equipped to thrive in the dynamic fields of Artificial Intelligence and Machine Learning. The program's curriculum, thoughtfully designed to align with industry trends, empowers students with practical knowledge and hands-on experience. This strategic approach reflects in the remarkable placements the program achieves year after year. Renowned tech companies, both national and international, actively seek UPES graduates for their expertise in AI and ML applications. The impressive placement record underscores the program's success in preparing students for rewarding careers, cementing UPES's reputation as a premier institution for those aspiring to make a significant impact in the domains of Electronics, Computer Engineering, Artificial Intelligence, and Machine Learning.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Semester 1
Course | L | T | P | Credits |
---|---|---|---|---|
Managing Self | 2 | 0 | 0 | 2 |
Environment and Climate Change | 2 | 0 | 0 | 2 |
Engineering Mathematics I | 3 | 1 | 0 | 4 |
Physics | 3 | 1 | 2 | 5 |
Programming for Engineers | 1 | 0 | 4 | 3 |
Basic Electrical and Electronics Engineering | 3 | 0 | 2 | 4 |
TOTAL | 20 |
Semester 2
Course | L | T | P | Credits |
---|---|---|---|---|
Time & Priority Management | 2 | 0 | 0 | 2 |
Environment and Climate Change | 2 | 0 | 0 | 2 |
Analog Electronics I | 3 | 0 | 0 | 3 |
Engineering Mathematics II | 3 | 1 | 0 | 4 |
Workshop Practice | 1 | 0 | 2 | 2 |
Engineering Graphics | 1 | 0 | 2 | 2 |
Digital Logic and Computer Design | 3 | 0 | 0 | 3 |
Chemistry | 3 | 0 | 0 | 3 |
Design and Build Lab | 0 | 0 | 2 | 1 |
TOTAL | 22 |
Semester 3
Course | L | T | P | Credits |
---|---|---|---|---|
Exploratory 1 | 3 | 0 | 0 | 3 |
Communication Skills (Oral) | 2 | 0 | 0 | 2 |
Data Structure | 3 | 0 | 2 | 4 |
Signals and Systems | 3 | 0 | 0 | 3 |
Analog Electronics-II | 3 | 0 | 2 | 4 |
Digital System Design | 3 | 0 | 2 | 4 |
Social Internship | 0 | |||
TOTAL | 20 |
Semester 4
Course | L | T | P | Credits |
---|---|---|---|---|
Communication Skills (Written) | 2 | 0 | 0 | 2 |
Exploratory 2 | 3 | 0 | 0 | 3 |
Database Management System | 3 | 0 | 2 | 4 |
Communication System | 3 | 0 | 2 | 4 |
Operating system | 3 | 0 | 2 | 4 |
Probability & Statistics | 3 | 0 | 0 | 3 |
Machine learning with Python | 0 | 0 | 4 | 2 |
TOTAL | 22 |
Semester 5
Course | L | T | P | Credits |
---|---|---|---|---|
Technologies of Future/Meta 101 | 2 | 0 | 0 | 2 |
Working with People | 2 | 0 | 0 | 2 |
Exploratory 3 | 3 | 0 | 0 | 3 |
Design and Analysis of Algorithm | 3 | 0 | 2 | 4 |
Microprocessors and Microcontrollers | 3 | 0 | 2 | 4 |
VLSI Design | 3 | 0 | 2 | 4 |
Capstone I | 2 | |||
TOTAL | 21 |
Semester 6
Course | L | T | P | Credits |
---|---|---|---|---|
Deepening Self | 2 | 0 | 0 | 2 |
Exploratory 4 | 3 | 0 | 0 | 3 |
Specialization Course I | 3 | 0 | 0 | 3 |
Advanced Programming | 2 | 0 | 2 | 3 |
Embedded Systems and IoT | 3 | 0 | 2 | 4 |
Specialization Course II | 3 | 0 | 0 | 3 |
Capstone II | 2 | |||
Industrial visit | 0 | |||
TOTAL | 20 |
Semester 7
Course | L | T | P | Credits |
---|---|---|---|---|
Exploratory 5 | 3 | 0 | 0 | 3 |
Agile Software Engineering | 3 | 0 | 2 | 4 |
Data Communication and Networking | 3 | 0 | 2 | 4 |
Specialization Course III | 3 | 0 | 0 | 3 |
Specialization Course IV | 3 | 0 | 0 | 3 |
Major Project I | 2 | |||
Industrial Internship | 1 | |||
TOTAL | 20 |
Semester 8
Course | L | T | P | Credits |
---|---|---|---|---|
Exploratory 6 | 3 | 0 | 0 | 3 |
Specialization Course V | 3 | 0 | 0 | 3 |
Digital Signal Processing | 3 | 0 | 0 | 3 |
Mobile and Web Application | 3 | 0 | 0 | 3 |
Major Project II | 6 | |||
E-Waste Management and Recycling | 2 | 0 | 0 | 2 |
TOTAL | 20 |
Specialization Courses
Sem | Course | L | T | P | Credits |
---|---|---|---|---|---|
6th | Data Science | 3 | 0 | 0 | 3 |
6th | Soft Computing Techniques | 3 | 0 | 0 | 3 |
7th | Artificial Intelligence | 3 | 0 | 0 | 3 |
7th | Deep Learning | 3 | 0 | 0 | 3 |
8th | Natural Language Processing | 3 | 0 | 0 | 3 |
Eligibility
Interested students must meet the following minimum eligibility criteria for admission to the B.Tech. program in Electronics & Computer Engineering (AI & ML Applications): Minimum 50% marks in Classes X and XII. with 50% in PCM (Physics/Chemistry and Mathematics) in Class XII.
Selection Criteria
The criteria for selecting students who wish to pursue B.Tech. in Electronics & Computer Engineering (specializing in AI & ML Applications) at UPES School of Advanced Engineering depend on the performance in UPESEAT / JEE / Board Merit / SAT/ CUET.
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